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Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases
Open accessAbstract
Complex and dynamic networks of molecules are involved in human diseases. High-throughput technologies enable omics studies interrogating thousands to millions of makers with similar biochemical properties (eg, transcriptomics for RNA transcripts). However, a single layer of "omics" can only provide limited insights into the biological mechanisms of a disease. In the case of genome-wide association studies, although thousands of single nucleotide polymorphisms have been identified for complex diseases and traits, the functional implications and mechanisms of the associated loci are largely unknown. Additionally, the genomic variants alone are not able to explain the changing disease risk across the life span. DNA, RNA, protein, and metabolite often have complementary roles to jointly perform a certain biological function. Such complementary effects and synergistic interactions between omic layers in the life course can only be captured by integrative study of multiple molecular layers. Building upon the success in single-omics discovery research, population studies started adopting the multi-omics approach to better understanding the molecular function and disease etiology. Multi-omics approaches integrate data obtained from different omic levels to understand their interrelation and combined influence on the disease processes. Here, we summarize major omics approaches available in population research, and review integrative approaches and methodologies interrogating multiple omic layers, which enhance the gene discovery and functional analysis of human diseases. We seek to provide analytical recommendations for different types of multi-omics data and study designs to guide the emerging multi-omic research, and to suggest improvement of the existing analytical methods.
Verified 2026-10-05 · 1 reference not checked yet
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80 Not checked yet · 58 Own interpretation · 21 No basis given · 3 Sources not found · 1 Supported
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In the paper
“Incorporating multi-omic measures of population samples into multidimensional network and system analyses (Figure 1), will address the gaps in our current knowledge of molecular mediation mechanisms, gene-environment interactions, and longitudinal effects during the development of chronic diseases”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 1. Introduction
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, emphasizing only one omic layer can miss important information, particularly the complementary effects and interactions between omic layers.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies
plainconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“However, a single layer of ‘omics’ can only provide limited insights into the biological mechanisms of a disease.”
- Also stated in: § 1. Introduction · plain
“the cross-talk between multiple molecular layers cannot be assessed by such simplified reduction approach”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > Abstract
What the sources say
- Not checked yetcites Chen et al., 2012 source
plain- Asserted: passes — The authors put it forward as true.
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- Also stated in: § 1. Introduction · plain
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In the paper
“Studying the epigenome in the well-characterized samples may enable us to discover novel genes and pathways through which genetic factors and environmental exposures influence disease initiation and development, and thereby provide new targets for prevention and treatment”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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- Based: passes — The paper gives a reason why it holds.
In the paper
“The group of correlated epigenetic and metabolic markers influenced by common environmental exposures suggest their potential utility in studying the environmental risk and gene-environmental interaction for human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Petersen et al., 2014 source
hedgedcorrelationaln = 1,814- Asserted: passes — The authors put it forward as true.
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In the paper
“the relationship between DNA methylation and Gene expression levels have been integrated at the genome-wide scale (Gibbs et al., 2010; Liu, Ding, et al., 2013).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Gibbs et al., 2010 source
- Not checked yetcites Liu, Ding, et al., 2013
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Using hundreds to thousands of subjects, these EWAS identified DNAm sites with much larger effect sizes compared to a typical GWAS of the same trait (Demerath et al., 2015; Dick et al., 2014).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, lack of correlation between epigenetic variation and gene expression levels does not mean that the epigenetic modifications have no functional consequence in gene expression.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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In the paper
“In a recent study, the associations between 649 metabolic traits and over 400,000 DNA methylation markers were examined using blood samples from 1,814 European participants. The epigenome-wide association approach revealed strong associations with metabolic traits driven by either genetic effects or possible environmental factors (Petersen et al., 2014).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Petersen et al., 2014 source
hedgedcorrelationaln = 1,814- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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In the paper
“numerous studies have successfully identified leukocyte-based DNAm markers associated with disease traits (Demerath et al., 2015; Dick et al., 2014; Hidalgo et al., 2014; Irvin et al., 2014; Liang et al., 2015; Liu, Aryee, et al., 2013).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Probably not a substantial claim. 47
- It may state two separate claims as one. 54
- The quote only partly states this claim. 1
Every source the paper cites for this claim was checked and supports it.
In the paper
“This chemical conversion does not distinguish 5-methylcytosine (5mC) from 5-hydroxymethylcytosine (5hmC) (Jin, Kadam, & Pfeifer, 2010)”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Supportedcites Jin et al., 2010 source
The Discussion states that sodium bisulfite sequencing and related approaches cannot distinguish 5mC from 5hmC. The Results likewise report that both modified bases remain distinguishable from unmodified cytosine after bisulfite treatment, but not from each other. (LLM, conf=0.95)
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
None of the sources cited for this claim have been checked yet.
In the paper
“RNA-Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.1 Genome-wide association study (GWAS) and transcriptomics studies of human diseases
What the sources say
- Not checked yetcites Ozsolak & Milos, 2011
- Not checked yetcites Z. Wang et al., 2009 source
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
In the paper
“Similarly, NGS technology has been used to call SNP genotypes and structural variations and provides the ultimate coverage and resolution of genetic variations including private mutations of individuals.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.1 Genome-wide association study (GWAS) and transcriptomics studies of human diseases
What the sources say
- Not checked yetcites Nielsen et al., 2011 source
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“thousands of genetic variants have been linked with hundreds of human traits and diseases (Welter et al., 2014).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.1 Genome-wide association study (GWAS) and transcriptomics studies of human diseases
What the sources say
- Not checked yetcites Welter et al., 2014 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The integrative approach of multi-omic data may enhance the understanding of the molecular dynamics underlying the pathophysiology of diseases, and may lead to novel strategies for early detection, prevention and treatment of human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 1. Introduction
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Proteomics measures all proteins and peptides in biological samples, and offers highly complementary information to genomics. As many biological functions are transmitted through proteins, proteomics can yield new biology and insights into disease.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“For both GWAS and transcriptomic studies, the next generation sequencing (NGS) technologies provide the most complete genome-wide coverage (Metzker, 2010).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.1 Genome-wide association study (GWAS) and transcriptomics studies of human diseases
What the sources say
- Not checked yetcites Metzker, 2010 source
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The new multi-omic studies will provide a combined view of multiple functional layer at a system level, and pave the road to precision medicine”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Epigenetic modifications, through DNA methylation (DNAm) and other mechanisms, can regulate gene expression and exert a long-term impact on the development of chronic diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Bird, 2007 source
- Not checked yetcites Foley et al.
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DNA, RNA, protein, and metabolite often have complementary roles to jointly perform a certain biological function. Such complementary effects and synergistic interactions between omic layers in the life-course can only be captured by integrative study of multiple molecular layers.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“GWAS have successfully identified the genetic susceptibility of human diseases, however, it cannot capture the intra-individual changes over time and how such changes relate to the disease risk”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Although each omics technology is capable of measuring one type of biomolecule accurately and comprehensively, by themselves, they are all limited by the functional roles of each type of molecule in a biological system.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“On the down side, it only represents ~2% of all DNAm sites of the human genome, and over-represents the genic regions (75% of sites) including promoter, gene body and 3’-UTR (Sandoval et al., 2011).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Sandoval et al., 2011 source
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Epigenetic modifications are shaped by environmental (e.g. smoking (Breitling, Yang, Korn, Burwinkel, & Brenner, 2011; Shenker et al.; Sun, 2014; Sun, Smith, et al., 2013), poor nutrition(Waterland & Jirtle, 2003), genetic factors (Sun, 2014; D. Zhang et al., 2010), and age – all well known risk factors human diseases”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
boosteddirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The 450K chip offers accurate and reproducible performance (Bibikova et al., 2011; Sandoval et al., 2011) with known but adjustable bias between Infinium I and II assays (Dedeurwaerder et al., 2011).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
In the paper
“But these sequencing-based methods suffer from unique technical biases and variations in sample preparation, processing and experimental procedures, which may not be fully addressable in the statistical analyses or require intensive bioinformatic/biostatistical analyses (Michels et al., 2013).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Michels et al., 2013 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“They provide better genomic coverage than 450K array, and can assess the genetic variants and allele-specific methylation beyond the preselected microarray probes.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Additionally, inflammatory markers have been associated with epigenetics at the gene level in peripheral leukocytes (Sun, Lazarus, et al., 2013; Uddin et al., 2011), which play a critical role in acute and chronic inflammation related to pathophysiology of many human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Sun, Lazarus, et al., 2013
- Not checked yetcites Uddin et al., 2011 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These omics-specific procedures for obtaining high-quality data are essential for the success of the multi-omics study.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Proteomics can also measure where and when proteins localize in the cell or tissue, that is important to understand the disease process but cannot be captured by other genomic technologies.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although epigenetic markers can induce the transcriptional regulation, the epigenetic modification may not be sufficient to cause changes of gene expression levels. In other words, epigenetic modifications potentiate the gene expression changes conditional on other co-regulators.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
hedgedconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
In the paper
“Thus, proteomics is positioned to define the functional roles of proteins in normal and disease-related cellular processes, and to enable hypothesis-driven and discovery research of human diseases (Nilsson et al., 2010).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Nilsson et al., 2010 source
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Recently, the protein products of 17,294 genes were identified and mapped in the draft of human proteome using 30 human samples of tissues and cells (Kim et al., 2014).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Kim et al., 2014 source
plainn = 30- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The technological advance in mass spectrometry (MS) and protein separation now allows rapid and accurate detection of hundreds of human proteins and peptides from a small amount of body fluid or tissue (Kraemer et al., 2011).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Kraemer et al., 2011 source
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Individual proteins can span 10 orders of magnitude in abundance (e.g. serum albumin and interleukin 6) (Anderson & Anderson, 2002).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Anderson & Anderson, 2002
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Proper procedures in sample collection, sample preparation, MS experiments and data analysis are all critical to obtain high-quality data for hypothesis-driven or proteome-wide discovery research (Nilsson et al., 2010).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Nilsson et al., 2010 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Despite these encouraging findings from the first wave of EWAS of disease traits, numerous issues such as imperfect epityping technologies, limited types of specimens from human subjects, cell-type specificity, sample size and data analysis framework need to be further addressed and improved (Heijmans & Mill, 2012).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.2 Epigenome-wide association studies
What the sources say
- Not checked yetcites Heijmans & Mill, 2012
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“This draft proteome demonstrated the feasibility of building a complete human proteome encompassing over 200 cell types and all body fluids.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Kim et al., 2014 source
boosteddirectn = 30- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Although, highly abundant “housekeeping” proteins from 2,350 genes constitute approximately 75% of total protein mass, low-abundance proteins constitute the majority of the protein species in human (Kim et al., 2014).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
- Not checked yetcites Kim et al., 2014 source
plainn = 30- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although the use of blood as surrogate tissue is sometimes relevant (e.g. autoimmune diseases and inflammatory processes), the biological relevance of blood-based omic profiles may not be apparent for many human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.5 Common issues and limitations of omics approaches
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“A tissue sample always involves several cell types, each having a unique omic profile.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.5 Common issues and limitations of omics approaches
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Proteomics approach has been widely adopted in studies of human diseases including cancer (Frantzi et al., 2015; S. Pan, Brentnall, & Chen, 2015; Petricoin et al., 2002; Tsai et al., 2015), multiple sclerosis (Farias, Pradella, Schmitt, Santos, & Martins-de-Souza, 2014) and schizophrenia (Al Awam et al., 2015; Nascimento & Martins-de-Souza, 2015).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.3 Proteomic studies of human biology and diseases
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The tissue and cell type specificity leads to two important issues in multi-omics studies, selection of tissues and cell types, and heterogeneity of tissues.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.5 Common issues and limitations of omics approaches
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An alternative approach is to conduct initial association study using a large sample of mixed cell types adjusted for the effect of heterogeneity. Once an averaged effect is identified, a follow up study of the sorted cells can focus on a specific omic maker to identify the most relevant cell types.”
- Also stated in: § 2.5 Common issues and limitations of omics approaches · plain
“The analysis in the second stage does not require expensive omic profiling or large amount of samples, but provides direct inference on the molecular mechanism of a disease.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 2. Overview of omics technologies and association studies > 2.5 Common issues and limitations of omics approaches
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one. The quote only partly states this claim.
- Also stated in: § 2.5 Common issues and limitations of omics approaches · plain
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Key genes such as DNA methyltransferases (DNMTs) directly control the DNA methylation profile.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Most GWAS findings map to non-coding regions, but a large proportion map to ENCODE regulatory elements (Schaub, Boyle, Kundaje, Batzoglou, & Snyder, 2012), suggesting the important role of transcriptional regulation underlying human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Schaub, Boyle, Kundaje, Batzoglou, & Snyder, 2012
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other genetic variants may also influence the patterns of DNA methylation by modifying the accessibility or binding affinity of enzymes.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Disease-associated genetic variants do not directly cause disease at the molecular level. They affect intermediate phenotypes that in turn induce molecular and physiological changes.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, identifying the intermediate phenotypes of gene expression, DNA methylation, protein and metabolite levels that directly influence by genetic variants has the potential to provide the functional information of disease-causing genes and pathways, and to unravel the genetic-controlled molecular systems underlying the changes of health and disease status.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Several systems genetics studies of metabolites in human plasma or serum have been reported (Gieger et al., 2008; Kettunen et al., 2012; Shin et al., 2014; Suhre et al., 2011; Yu et al., 2013).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The national institute of health Roadmap Epigenomics Consortium generated 111 human reference epigenomes for primary cells and tissues, the largest collection so far (Roadmap Epigenomics et al., 2015).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Roadmap Epigenomics et al., 2015 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Metabolites play critical roles in biological pathways, and are partially controlled by genetic regulations.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Another population study of 8,330 European individuals analyzed 216 serum metabolites using NMR (Kettunen et al., 2012). The GWAS of these metabolites identified 31 mQTLs including 11 novel loci without known association with any traits or diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Kettunen et al., 2012 source
plaincorrelationaln = 8,330- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Early pQTL studies suffered from an inconsistent detection of proteins across samples and a limited dynamic range for low abundance proteins (Foss et al., 2007).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Foss et al., 2007 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The levels of a set of metabolites are strongly associated with genetic loci, and some of these loci overlapped with GWAS loci for disease traits.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because of the large number of SNP-DNA methylation site pairs to test, the trans-meQTL analysis is more computational intensive and requires a more stringent multiple-testing correction than the cis-meQTL analysis.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The MR approach uses the genetic variant mimicking the biological effects of a modifiable exposure.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Significant GWAS loci are enriched for e QTLs (Nicolae et al., 2010) and meQTLs (X. Zhang et al., 2014).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Picotti et al. used a nearly complete map of yeast proteome and genetic variation data to identify strong genetic effects of protein abundance, and to demonstrate epistatic interactions affecting protein levels (Picotti et al., 2013).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Picotti et al., 2013 source
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The pQTL analysis of mouse plasma identified strong genetic determinants for approximately 40% of tested proteins, and suggested causal genetic variants affecting abundance of plasma proteins (Holdt et al., 2013).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Holdt et al., 2013 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, these studies catalogued a large number of QTLs across multiple omic layers in multiple tissues and cell types, and provide a rich resource not only to understand the genetic regulation of intermediate phenotypes, but also to illustrate important molecular networks mediating the interaction between genetic variants and environment for human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“A GWAS of 42 proteins identified eight strong pQTLs with rather large effect sizes (0.19 to 0.69 standard deviations per allele). However, the panel of proteins only covered a small fraction of the proteome (Melzer et al., 2008).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Melzer et al., 2008 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“MR was initially proposed as an epidemiologic method to obtain unbiased estimates of the putative casual effects without conducting a randomized trial (Gray & Wheatley, 1991; Katan, 1986).”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
What the sources say
- Not checked yetcites Gray & Wheatley, 1991
- Not checked yetcites Katan, 1986 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“First, these QTLs have been used to infer the functional link between genetic variants and disease traits in recent GWAS, and lead to follow-up studies uncovering the biological functions of disease-associated loci.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.1 Genetic determinants of omic markers - studies of quantitative trait loci (QTL)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When the SNPs have no effect on the gene expression (i.e., not eQTL SNPs; αG = 0), then there is no IE of the SNPs on Y, so that the null hypothesis (3) is not equivalent to testing for no TE, but simply whether there exists a joint effect of the SNPs, the gene expression, and possibly their interactive effect on the disease risk.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The regression-based approach jointly models multi-omics data, using the framework of mediation analysis. These data are typically collected on the same subjects.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Another type of datasets is multi-omics data collected on different sets of individuals from different studies.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Both genetic and environmental factors contribute to the development of human diseases.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.2 Environmental influences on multi-omic markers
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The multi-omics approach thus holds the promises to further advance human disease research.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Different research questions can be answered for each type of multi-omic dataset using corresponding statistical approaches.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Existing studies in human and model organisms highlighted the complexity of genomic information flow and the interactive networks in biological processes and disease development.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“On the other hand, a comparable high-throughput approach to studying the environmental causes of human diseases remains unavailable, which leaves a large proportion of the phenotypic variance unexplained.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.2 Environmental influences on multi-omic markers
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The ideal datasets for such an integrative analysis are multi-omics data all collected on the same set of samples.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The non-genetic factors can cause important changes in proteins, nucleic acids, lipids and other biomolecules, which have direct roles in biochemical and cellular functions.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 3. Genetic and environmental determinants of epigenomic, transcriptomic, metabolomic and proteomic markers > 3.2 Environmental influences on multi-omic markers
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, this is often not possible because of the cost or because the control samples simply do not have the appropriate tissues to study.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Specifically, in GWAS, SNPs and the disease outcomes are collected, but not gene expression/methylation; in QTL studies, SNPs, gene expression and methylation are collected, but not the disease outcome.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If there exists an effect of G on E, ΔG→E→Y corresponds to βE, βME, βGE, and βGME; it means that the test of the hypothesis (7) is equivalent to the test of the IE of SNPs mediated through gene expression.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, the DE ΔG→Y corresponds to βG, βGM, βGE, and βGME, which is not influenced by the relationship among G, M, and E.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Zhao et al. (2014) considered the same omic datasets that Huang et al. (2014) have dealt with, i.e., SNP, gene expression, and disease data collected on the same set of subjects. However, Zhao et al. (2014) focused on testing the IE of the SNPs on the disease outcome that is regulated by gene expression.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
What the sources say
- Not checked yetcites Zhao et al. (2014) source
- Not checked yetcites Huang et al. (2014)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Note that the meQTL and eQTL studies should be conducted on the same subjects in order to calculate μME.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“This work is analogous to the work by Huang et al. (2014) but focuses solely on increasing the power of SNP association testing, rather than on assigning causal interpretations to any of the parameters.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
What the sources say
- Not checked yetcites Huang et al. (2014)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the eQTLs of the gene, which constitute a unique “genetic signature” of this gene, should overlap significantly with the set of loci associated with the disease.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although Uj and Vj are not observed, they are related to peQTL,j and pGWAS,j: when peQTL,j (pGWAS,j) is small, it is likely that Uj (Vj) = 1.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“To apply their method in an agnostic, genome-wide manner, they proposed to consider one gene in E at a time; to reduce the multiple testing burden imposed by the huge number of pairwise tests they proposed to restrict to testing only those SNPs located cis to each gene.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Model (9) is significantly different from model (2) in that the former does not consider the regulation of the SNP on the expression of an individual gene, but on one particular linear combination of them; it hence requires estimating fewer parameters.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“When a particular set of genes or a pathway is of interest such that the number of genes in E does not exceed the number of subjects, Zhao et al. (2014) proposed to use the standard estimating equation theory for inference.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.1 Regression-based joint modeling
What the sources say
- Not checked yetcites Zhao et al. (2014) source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Based on a phenotype-based permutation procedure that preserves LD structure in SNP data and gene-gene correlation structure in gene expression data, the false discovery rate (FDR) or the family-wise error rate (FWER) can be calculated and the significant gene sets are declared controlling for FDR or FWER below a certain threshold.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.3 Aggregating evidence of multi-omics data over gene set/pathway
What the sources say
- Not checked yetcites Xiong et al. (2012) source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“It has been implemented in a software program called Sherlock.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Under the null, P(TeQTL,j | Uj = 0) and P(TGWAS,j | Vj = 0) follow the standard normal distribution.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“To assess the statistical significance of BF, a simulation approach was proposed to compute the p-value of the BF for a gene.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When Z = 1 and Uj = 1, Vj should always be 1, as a true eQTL of the gene is expected to be associated with the disease.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- The authors state this as an assumption: In He et al.'s method, when Z = 1 and Uj = 1, Vj should always be 1, because a true eQTL of the gene is expected to be associated with disease.
In the paper
“Third, the gene set is evaluated by a weighted Kolmogorov-Smirnov (K-S) statistic (i.e., gene set association score) to determine whether the genes belonging to this gene set are preferentially near the top of the ranked ordered list based on gene association scores.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.3 Aggregating evidence of multi-omics data over gene set/pathway
What the sources say
- Not checked yetcites Xiong et al. (2012) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The gene expression data and the SNP genotype data are allowed to be collected on the same samples or different samples.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.3 Aggregating evidence of multi-omics data over gene set/pathway
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When Z = 0, the gene is irrelevant to the disease and thus Uj and Vj are independent.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When Z = 1 and Uj =0, this SNP is not an eQTL and thus Uj and Vj are also independent.”
§ Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases > 4. Analytical approaches and methods for multi-omic association studies > 4.2 Matching Patterns of eQTL and GWAS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
The functional implications and mechanisms of GWAS-associated loci are largely unknown.
“although thousands of SNPs have been identified for complex diseases and traits, the functional implications and mechanisms of the associated loci are largely unknown.”
The paper relies on this without support.
Genomic variants alone cannot explain changes in disease risk across the lifespan.
“Additionally, the genomic variants alone are not able to explain the changing disease risk across the life span.”
The paper relies on this without support.
DNA methylome is the only epigenomic mechanism that is robustly measured in population samples.
“We focus on DNA methylome in this article, because it is the only epigenomic mechanism being robustly measured in population samples.”
The paper relies on this without support.
Most human diseases arise from both genetic and environmental factors and from their interplay.
“Most human diseases are thought to be due to both genetic and environmental factors, and the interplay between genes and environment.”
The authors state this as an assumption.
In Zhao et al.'s two-stage model, the SNP affects disease risk through affecting gene expression levels.
“assuming that the SNP affects disease risk through affecting the gene expression levels.”
The authors state this as an assumption.
In He et al.'s method, when Z = 1 and Uj = 1, Vj should always be 1, because a true eQTL of the gene is expected to be associated with disease.
“When Z = 1 and Uj = 1, Vj should always be 1, as a true eQTL of the gene is expected to be associated with the disease.”
The authors state this as an assumption.
In Huang et al.'s variance component test, the components in βG are independent and follow an arbitrary distribution with mean 0 and variance τG, and the components in βGE are independent and follow an arbitrary distribution with mean 0 and variance GE.
“They assumed that the components in the vector βG are independent and follow an arbitrary distribution with mean 0 and variance τG, and that the components in βGE are independent and follow an arbitrary distribution with mean 0 and variance GE.”
The paper relies on this without support.
Multi-omics study has been hampered mainly by lack of feasible technologies for large-scale population studies, availability of biospecimens, and high cost.
“Despite of its appealing scientific gain, the materialization of the multi-omics study has been hampered mainly due to the lack of feasible technologies for large-scale population studies, availability of biospecimens and the high cost attached to them.”
The paper relies on this without support.
Core technologies behind high-throughput assays such as sequencing and mass spectrometry have become more sensitive, accurate, and affordable in recent years.
“In recent years, the core technologies behind the high-throughput assays, such as sequencing and mass spectrometry, have become more and more sensitive, accurate, and affordable.”
The paper relies on this without support.
Interrogation of complementary omics beyond a single omic layer has been explored for several diseases and model systems to demonstrate the utility and feasibility of multi-omics research.
“Interrogation of complementary omics beyond a single omic layer has been explored for several diseases and model systems to demonstrate the utility and feasibility of multi-omics research.”
The paper relies on this without support.
Current multi-omics research of human diseases demands a large amount of resources to carry out a population study.
“Current multi-omics research of human diseases demands a large amount of resources to carry out a population study.”
The paper relies on this without support.
Single-omic scans such as GWAS and EWAS continue to provide insights into the mechanism and etiology of human diseases.
“The thorough scan of a single type of biologically function features (e.g., GWAS and EWAS) continues to provide insights into the mechanism and etiology of human diseases.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“For example, a regression-based method termed “mediation analysis” was developed to integrate SNP and gene expression data, treating the gene expression as the mediator in the causal mechanism from SNPs to disease [45, 46].”
From Multi-omics approaches to disease (2017) · cites this paper as [46]
In the citing paper
“Similar approaches have been applied to other omics layers [46, 47].”
From Multi-omics approaches to disease (2017) · cites this paper as [46]
Citations
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
RNA-Seq: a revolutionary tool for transcriptomics
Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174
Trapnell, C., Roberts, A., Goff, L. A., Pertea, G. M., Kim, D., Kelley, D. R., Pimentel, H., Salzberg, S. L., Rinn, J. L., & Pachter, L. S. (2012) · Nature Protocols · doi:10.1038/nprot.2012.016 · Cited by 12,145
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Alizadeh, A. A., Eisen, M. B., Davis, R. E., Ma, C., Lossos, I. S., Rosenwald, A., Boldrick, J. C., Sabet, H., Tran, T., Yu, X., et al. (2000) · Nature · doi:10.1038/35000501 · Cited by 9,925
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
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Pietrantonio, N. D., Cappellacci, I., Mandatori, D., BALDASSARRE, M. P. A., Pandolfi, A., & Pipino, C. (2023) · Advanced Biology · doi:10.1002/adbi.202300172 · Cited by 10
Chen, S., Dong, Y., Aiheti, N., Wang, J., Yan, S., Kuribanjiang, K., Li, H., Peng, X., Wupuer, A., Li, Y., et al. (2024) · The Journals of Gerontology Series A · doi:10.1093/gerona/glae051 · Cited by 10
Sun, Y. V., Liu, C., Staimez, L. R., Ali, M. K., Chang, H. H., Kondal, D., Patel, S. A., Jones, D. P., Mohan, V., Tandon, N., et al. (2020) · Wellcome Open Research · doi:10.12688/wellcomeopenres.16336.2 · Cited by 13
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Zhou, J., Zhao, J., Li, R., Ke, Q., Wang, J., Li, Y., Hu, S., Zeng, J., Pu, F., Li, N., et al. (2025) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2025.110159 · Cited by 8
Wang, W., Zhou, C., Tang, H., Yu, Y., & Zhang, Q. (2020) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2020.00250 · Cited by 8
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Leak, T. S., Yan, F., & Daniels, P. V. (2021) · Current Diabetes Reports · doi:10.1007/s11892-021-01413-4 · Cited by 8
Danoy, M., Poulain, S., Jellali, R., Gilard, F., Kato, S., Plessy, C., Kido, T., Miyajima, A., Sakai, Y., & Leclerc, É. (2020) · Biochemical Engineering Journal · doi:10.1016/j.bej.2020.107490 · Cited by 9
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Cruz, A. K., Alves, M. A., Andrésson, Þ., Bayless, A. L., Bloodsworth, K., Bowden, J. A., Bullock, K. H., Burnet, M., Neto, F. C., Choy, A. H., et al. (2024) · Metabolomics · doi:10.1007/s11306-024-02185-0 · Cited by 7
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Wang, L., Sun, T., Liu, X., Wang, Y., Qiao, X., Chen, N., Liu, F., Zhou, X., Wang, H. X., & Shen, H. (2024) · Clinica Chimica Acta · doi:10.1016/j.cca.2023.117752 · Cited by 7
Meta-Analysis of Gene Expression Profiles in Acute Promyelocytic Leukemia Reveals Involved Pathways.
Jalili, M., Salehzadeh‐Yazdi, A., Mohammadi, S., Yaghmaie, M., Ghavamzadeh, A., & Alimoghaddam, K. (2017) · PubMed Central · Cited by 7
Identification of metabolite traits from the current metabolomic approaches
Omena-Garcia, R. P., Silva, L. D. Á., Vital, C. E., Araújo, W. L., Ramos, H. J. D. O., & Nunes‐Nesi, A. (2019) · Theoretical and Experimental Plant Physiology · doi:10.1007/s40626-019-00147-9 · Cited by 7
Tremblay, B. L., Guénard, F., Lamarche, B., Përusse, L., & Vohl, M. (2019) · Lifestyle Genomics · doi:10.1159/000503828 · Cited by 7
Monteiro, J. P., Maciel, E. A., Melo, T., Flanagan, C. A., Urbani, N., das Neves, J. P. C., & Domingues, M. R. (2021) · Lipids · doi:10.1002/lipd.12307 · Cited by 7
Genetics of atrial fibrillation—an update of recent findings
Manoharan, A., Ravikumar, S., & Ballambattu, V. B. (2022) · Molecular Biology Reports · doi:10.1007/s11033-022-07420-2 · Cited by 7
Liu, X., Jiang, L., Zhang, W., Zhang, J., Luan, X., Zhan, Y., Wang, T., Da, J., Liu, L., Zhang, S., et al. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04275-4 · Cited by 8
Kimura, S., & Harashima, H. (2024) · BioDrugs · doi:10.1007/s40259-024-00647-4 · Cited by 8
Pesquisa translacional na era pós-genômica: avanços na área da transcriptômica
Pacheco, C., Ceccatto, V. M., Maia, C. M., Rosa, S. D. S. R. F., & Leite, C. R. M. (2019) · Saúde em Debate · doi:10.1590/0103-11042019s213 · Cited by 7
Machine Learning Improves Analysis of Multi-Omics Data in Aging Research and Geroscience
Chen, L. (2021) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2021.104360 · Cited by 7
Editorial: The role of multi-omics variants in tumor immunity and immunotherapy
Chen, S., Xu, H. M., Guo, C., Liu, Z., & Han, X. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1098825 · Cited by 7
Breast cancer pathogenesis, diagnosis and treatment: a comprehensive review
Pasi, D., Aswathy, B., Das, M., & Agrawal, P. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1773232 · Cited by 11
Bonnechère, B. (2022) · Genes · doi:10.3390/genes14010063 · Cited by 7
Using GMQL-Web for Querying, Downloading and Integrating Public with Private Genomic Datasets
Settino, M., Bernasconi, A., Ceddia, G., Agapito, G., Masseroli, M., & Cannataro, M. (2019) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/3307339.3343466 · Cited by 6
Jin, Z., Zhang, J., Wu, X., & Cao, G. (2019) · RSC Advances · doi:10.1039/c8ra05528a · Cited by 6
Bioinformatic Approaches in the Understanding of Mechanism of Action ( MoA )
Trapotsi, M., Barrett, I. P., Engkvist, O., & Bender, A. (2019) · Methods and principles in medicinal chemistry · doi:10.1002/9783527818242.ch11 · Cited by 6
Huang, X., Yang, Q., Yan, Z., Wang, P., Shi, H., Li, J., Shang, X., & Gun, S. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.803477 · Cited by 5
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Anyaegbunam, U. A., Vagiona, A.-C., ten Cate, V., Bauer, K., Schmidlin, T., Distler, U., Tenzer, S., Araldi, E., Bîndilă, L., Wild, P. S., et al. (2025) · Biomolecules · doi:10.3390/biom15040484 · Cited by 5
Nam, S. L., Carrillo, K. S. T., de la Mata, A. P., & Harynuk, J. J. (2023) · Metabolites · doi:10.3390/metabo13070828 · Cited by 5
Tan, Y., Yao, B., Kang, Y., Shi, S., Shi, Z., & Su, J. (2024) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2023.115902 · Cited by 5
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Ferreri, C., Sansone, A., Ferocino, A., Tueros, I., & Martinez, S. A. (2022) · Biomarkers in disease · doi:10.1007/978-3-030-81304-8_26-1 · Cited by 5
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Maru, D., & Kumar, A. (2024) · Sustainable agriculture reviews · doi:10.1007/978-3-031-54372-2_1 · Cited by 5
Jang, M., Lee, S.-H., & Kim, J. (2025) · Springer eBooks · doi:10.1007/978-981-97-7395-4_5 · Cited by 5
Yang, T., Wei, P., & Pan, W. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa898 · Cited by 5
Pan, J., Ma, B., Hou, X., Li, C., Xiong, T., Gong, Y., & Song, F. (2022) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2022576 · Cited by 5
Systems biology and network medicine: An integrated approach to redox biology and pathobiology
Lee, L. Y.-H., & Loscalzo, J. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-818606-0.00003-1 · Cited by 5
Ma, C., Zhao, J., Xu, X., He, X.-L., Qin, S., & Zhou, J.-Y. (2025) · Discover Oncology · doi:10.1007/s12672-025-03077-y · Cited by 4
Shen, L.-M., Gao, F., Wei, J., Gao, D., Qin, D.-L., Wang, X., Ji, Y.-J., An, X., Zhou, X.-G., Wu, J.-M., et al. (2025) · Trends in Analytical Chemistry (TrAC) · doi:10.1016/j.trac.2025.118498 · Cited by 2
AI-assisted integretomics approaches in plant stress research
Singh, T. (2026) · Journal of Plant Biochemistry and Biotechnology · doi:10.1007/s13562-026-01048-0 · Cited by 4
Dong, J., Sun, M., Li, Y., & Xie, Z. (2025) · Journal of drug targeting · doi:10.1080/1061186x.2025.2544786 · Cited by 4
Eknure, C., Agarwal, A. P., Bachhav, Y. G., & Kumar, M. S. (2025) · World Journal of Microbiology and Biotechnology · doi:10.1007/s11274-025-04671-6 · Cited by 5
Huang, Y., Chen, R., Yang, S., Chen, Y., & Lü, X. (2022) · Journal of Biomedical Nanotechnology · doi:10.1166/jbn.2022.3365 · Cited by 4
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Ait-El-Mokhtar, M., & Baslam, M. (2023) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2023.1151367 · Cited by 4
Siavrienė, E., Petraitytė, G., Mikštienė, V., Maldžienė, Ž., Sasnauskienė, A., Žitkutė, V., Ambrozaitytė, L., Rančelis, T., Utkus, A., Kučinskas, V., et al. (2023) · Medicina · doi:10.3390/medicina59071225 · Cited by 4
Trends in the application of “omics” to Alzheimer’s disease: a bibliometric and visualized study
Tan, Y., Nie, D., Cao, Y., Ke, C., Pan, J., Shi, W. Y., & Zhang, W. (2023) · Neurological Sciences · doi:10.1007/s10072-023-07079-y · Cited by 4
Recent advances in proteomic-based diagnostics of cystic fibrosis
Nimer, R. M., & Rahman, A. M. A. (2023) · Expert Review of Proteomics · doi:10.1080/14789450.2023.2258282 · Cited by 4
Parmar, R., Pickering, H. C., Ahn, R. S., Rossetti, M. M., Gjertson, D. W., Ruffin, F., Chan, L. C., Fowler, V. G., Yeaman, M. R., Reed, E. F., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1373553 · Cited by 4
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Kellett, S. K., & Masterson, J. C. (2024) · Journal of Leukocyte Biology · doi:10.1093/jleuko/qiae126 · Cited by 5
Zhang, H., Jiang, W., Jiang, Y., Xu, N., Nong, L., Li, T., & Liu, R. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1447152 · Cited by 4
Integrative multi-omics analysis to gain new insights into COVID-19
Eshetie, S., Choi, K. W., Hyppönen, E., Benyamin, B., & Lee, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-79904-z · Cited by 4
Wang, Y., Junda, W. U., Mingying, N. I. E., HUANG, L., Peiheng, S. U. N., Jianyun, Z. H. A. N., Jianfu, W. U., Shiyu, L. I. U., Yuan, C., Longsong, H. U., et al. (2025) · Scientia Horticulturae · doi:10.1016/j.scienta.2025.113971 · Cited by 4
Zhu, X., Li, F., Wang, M., Su, H., Wu, X., Qiu, H., Zhou, W., Shan, C., Wang, C., & Wei, L. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.672498 · Cited by 4
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Liu, C., & Sun, Y. V. (2021) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2021.05.011 · Cited by 4
Self-citationLuan, G., Wang, M., Yuan, J., Bu, X., Song, J. K., Wang, C., & Zhang, L. (2022) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-022-03967-6 · Cited by 4
Yada, S., Tanaka, R., Cheng, F., Aramaki, E., & Kurohashi, S. (2022) · Journal of Natural Language Processing · doi:10.5715/jnlp.29.1165 · Cited by 4
Susceptibility identification for seasonal influenza A/H3N2 based on baseline blood transcriptome
Tang, J. Y., Xu, Q., Tang, K., Ye, X., Cao, Z., Zou, M., Zeng, J., Guan, X., Han, J., Wang, Y., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1048774 · Cited by 4
Zhu, Z., Chen, X., Zhang, S., Yu, R., Qi, C., Cheng, L., & Zhang, X. (2023) · Human Genetics · doi:10.1007/s00439-023-02602-9 · Cited by 5
Lucena-Padros, H., Bravo‐Gil, N., Tous, C., Rojano, E., Seoane, P., Fernández, R. M., Ranea, J. A. G., Antiñolo, G., & Borrego, S. (2024) · Biomolecules · doi:10.3390/biom14020164 · Cited by 5
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Martínez-Espinosa, R. (2017) · Journal of Clinical Microbiology and Biochemical Technology · doi:10.17352/jcmbt.000018 · Cited by 4
The Potential of Pharmacogenomics to Advance Kidney Disease Treatment
Birdwell, K. A., & Chung, C. P. (2017) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.05170517 · Cited by 4
Li, Z., Chen, Y., Zhang, Y., Fang, J., Xu, Z., Zhang, H., Mao, M., Zhang, L., & Pian, C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.03.494777 · Cited by 4
Integrative Multi-Omics Approaches for Identifying Cervical Cancer Therapeutic TargetsPreprint
Duppala, S. K., Yadala, R., Velingkar, A., Suravajhala, P., Pawar, S. C., & Vuree, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.07.511244 · Cited by 4
Gao, M., Shen, Y., Yang, P. C., Yuan, C., Sun, Y., & Li, Z. (2024) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2024.1414089 · Cited by 3
Self-citationCiantar, J., Marttila, S., Rajić, S., Kostiniuk, D., Mishra, P. P., Lyytikäinen, L., Mononen, N., Kleber, M. E., März, W., Kähönen, M. A. P., et al. (2024) · Epigenetics · doi:10.1080/15592294.2024.2397297 · Cited by 4
Multi-omics integration in disease research
Ceballos, M. W. G., Sy, F., Akbar, A., & Taofiq, A. (2025) · Progress in brain research · doi:10.1016/bs.pbr.2025.08.012 · Cited by 4
Huang, W., Lin, R., Zeng, X., Wang, H., & Yan, J. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1665688 · Cited by 4
Fan, H., Zhang, J., Zou, B., & He, Z. (2022) · Archives of Iranian Medicine · doi:10.34172/aim.2022.72 · Cited by 3
Chaithanya, P., & Meshram, R. J. (2023) · Cureus · doi:10.7759/cureus.42558 · Cited by 3
Omics approach for personalized and diagnostics medicine
Verma, D., & Kapoor, S. S. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-16092-9.00011-4 · Cited by 3
Ambikan, A. T., Akusjärvi, S. S., Sperk, M., & Neogi, U. (2024) · Advances in immunology · doi:10.1016/bs.ai.2024.08.002 · Cited by 5
Revisiting threats associated with neglected and emerging fungal pathogens in sub-Saharan Africa
Akinola, S. A., Adeyemo, R. O., Bale, M. I., Eilu, E., Afodun, A. M., Akinola, R. A. A., Binuyo, M. O., Odoma, S., Suleiman, I. E., Adegboyega, T. T., et al. (2024) · Discover Public Health · doi:10.1186/s12982-024-00318-3 · Cited by 3
Paromomycin targets HDAC1-mediated SUMOylation and IGF1R translocation in glioblastoma
Min, Z., Guo, Y., & Ning, L. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1490878 · Cited by 3
Masedunskas, A., Ciutiis, I. D., Hein, L. K., Ge, A., Kong, Y. X., Qi, M., Mainali, D., Rogerson‐Wood, L., Kroeger, C. M., Candia, Y. A., et al. (2024) · Nutrients · doi:10.3390/nu16244297 · Cited by 3
Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment
Bukhari, I., Li, M., Li, G., Xu, J., Zheng, P., & Chu, X. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1520398 · Cited by 3
Neu, J. (2018) · Avery's Diseases of the Newborn · doi:10.1016/b978-0-323-40139-5.00075-9 · Cited by 3
Levy, J., Silva, A. M., Carli, E. D., Cacau, L. T., de Alvarenga, J. F. R., Fiamoncini, J., Benseñor, I. M., Lotufo, P. A., & Marchioni, D. M. L. (2022) · Journal of Nutrition · doi:10.1093/jn/nxac115 · Cited by 3
Vitório, J. G., Duarte‐Andrade, F. F., Pereira, T. D. S. F., Melo‐Braga, M. N., Canuto, G. A. B., de Macedo, A. N., Lebron, Y. A. R., Moreira, V. R., Felicori, L. F., Lange, L. C., et al. (2022) · Journal of Oral Pathology and Medicine · doi:10.1111/jop.13327 · Cited by 3
Soluble CD14-associated DNA methylation sites predict mortality among men with HIV infection
Titanji, B. K., Wang, Z., Chen, J., Hui, Q., So‐Armah, K., Freiberg, M. S., Justice, A. C., Ke, X., Marconi, V. C., & Sun, Y. V. (2022) · AIDS · doi:10.1097/qad.0000000000003279 · Cited by 4
Self-citationMorin, L., Lecureur, V., & Lescoat, A. (2024) · Particle and Fibre Toxicology · doi:10.1186/s12989-024-00573-x · Cited by 3
Drug repurposing for neurodegenerative diseases
Shukla, H., John, D., Banerjee, S., & Tiwari, A. K. (2024) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2024.03.035 · Cited by 3
Sokouti, B., & Amjad, E. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-22326-6.00016-x · Cited by 3
Kethu, S. S., Natarajan, D. R., Narla, S., Valivarthi, D. T., & Peddi, S. (2025) · Journal of Information Technology and Digital World · doi:10.36548/jitdw.2024.4.007 · Cited by 3
Metadata
- Authors
- Sun, Y. V., & Hu, Y.-J.
- Affiliations
- Emory University (US)
- Corresponding author
- Sun, Yan V.
- Venue
- Advances in Genetics
- Publisher
- Elsevier
- Published
- 2016
- Volume
- 93
- Pages
- 147-190
- ISSN
- 0065-2660 (ISSN-L)
- PMC
- PMC5742494
- OpenAlex
- W2276765849
- Cited by
- 459
- References
- 159
- Citations by year
- 2026: 28 · 2025: 51 · 2024: 79 · 2023: 48 · 2022: 70 · 2021: 63 · 2020: 43 · 2019: 39 · 2018: 24 · 2017: 11 · 2016: 3
- FWCI
- 31.82
- Type
- book chapter
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Advances in genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- American Heart Association (13GRNT17060002)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Keywords
- multi-omics integration, complex diseases, gene discovery, functional genomics, etiology, single nucleotide polymorphisms, genome-wide association study, life course, population genetics
- MeSH terms
- Data Interpretation, Statistical, Disease, Environmental Exposure, Genetic Markers, Humans, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Proteomics, Genome-Wide Association Study, Metabolomics, Epigenomics, Transcriptome
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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