The study of eQTL variations by RNA-seq: from SNPs to phenotypes

Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556

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

TopHat: discovering splice junctions with RNA-Seq

Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,682

Alternative isoform regulation in human tissue transcriptomes

Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181

Minimum information about a microarray experiment (MIAME)-toward standards for microarray data

Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C. A., Causton, H. C., et al. (2001) · Nature Genetics · doi:10.1038/ng1201-365 · Cited by 4,109

Potential etiologic and functional implications of genome-wide association loci for human diseases and traits

Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013

Expansion of the eukaryotic proteome by alternative splicing

Nilsen, T. W., & Graveley, B. R. (2010) · Nature · doi:10.1038/nature08909 · Cited by 2,270

ChIP–seq: advantages and challenges of a maturing technology

Park, P. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2641 · Cited by 2,217

Maximum Entropy Modeling of Short Sequence Motifs with Applications to RNA Splicing Signals

Yeo, G. W.-M., & Burge, C. B. (2004) · Journal of Computational Biology · doi:10.1089/1066527041410418 · Cited by 2,042

Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease

Botstein, D., & Risch, N. (2003) · Nature Genetics · doi:10.1038/ng1090 · Cited by 1,503

Novel Insights into the Regulatory Architecture of CD4+ T Cells in Rheumatoid Arthritis

Aterido, A., Palacio, C., Marsal, S., Avila-Pedretti, G., & Julià, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0100690 · Cited by 26

Genome‐wide expression quantitative trait locus analysis in a recombinant inbred line population for trait dissection in peanut

Huang, L., Liu, X., Pandey, M. K., Ren, X., Chen, H., Xue, X., Liu, N., Huai, D., Chen, Y., Zhou, X., et al. (2019) · Plant Biotechnology Journal · doi:10.1111/pbi.13246 · Cited by 26

Use of Functional Genomics to Identify Candidate Genes Underlying Human Genetic Association Studies of Vascular Diseases

Yang, X. (2012) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.111.232702 · Cited by 25

Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data

Wood, D., Nones, K., Steptoe, A. L., Christ, A. N., Harliwong, I., Newell, F., Bruxner, T. J. C., Miller, D. K., Cloonan, N., & Grimmond, S. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0126911 · Cited by 26

Genetic architecture of the metabolic pathway of salicylic acid biosynthesis in Populus

Xiao, L., Du, Q., Fang, Y., Quan, M., Lu, W., Wang, D., Si, J., El-Kassaby, Y. A., & Zhang, D. (2021) · Tree Physiology · doi:10.1093/treephys/tpab068 · Cited by 22

The genetic diversity and nutritional quality of proso millet (Panicum miliaceum) and its Philippine ecotype, the ancient grain “kabog millet”: A review

Narciso, J. O., & Nyström, L. (2023) · Journal of Agriculture and Food Research · doi:10.1016/j.jafr.2023.100499 · Cited by 22

Gene-Gene Interaction and Functional Impact of Polymorphisms on Innate Immune Genes in Controlling Plasmodium falciparum Blood Infection Level

Basu, M., Das, T., Ghosh, A., Majumder, S., Maji, A. K., Kanjilal, S. D., Mukhopadhyay, I., Roychowdhury, S., Banerjee, S., & Sengupta, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046441 · Cited by 22

Compensatory trans -regulatory alleles minimizing variation in TDH3 expression are common within Saccharomyces cerevisiae

Metzger, B. P. H., & Wittkopp, P. J. (2019) · Evolution Letters · doi:10.1002/evl3.137 · Cited by 21

Approach to epigenetic analysis in language disorders

Smith, S. D. (2011) · Journal of Neurodevelopmental Disorders · doi:10.1007/s11689-011-9099-y · Cited by 21

Genetic evidence for a causal relationship between type 2 diabetes and peripheral artery disease in both Europeans and East Asians

Xiu, X., Zhang, H., Xue, A., Cooper, D. N., Li, Y., Yang, Y., Yang, Y., & Zhao, H. (2022) · BMC Medicine · doi:10.1186/s12916-022-02476-0 · Cited by 24

Towards a map of cis-regulatory sequences in the human genome

Niu, M., Tabari, E. S., Ni, P., & Su, Z. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky338 · Cited by 19

A Functional SNP Catalog of Overlapping miRNA-Binding Sites in Genes Implicated in Prion Disease and Other Neurodegenerative Disorders

Saba, R., Medina, S. J., & Booth, S. A. (2014) · Human Mutation · doi:10.1002/humu.22627 · Cited by 19

Exhaustive database searching for amino acid mutations in proteomes

Hyatt, D., & Pan, C. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts274 · Cited by 18

IRF6 rs2235371 as a risk factor for non-syndromic cleft palate only among the Deutero-Malay race in Indonesia and its effect on the IRF6 mRNA expression level

Nasroen, S. L., Maskoen, A. M., Soedjana, H., Hilmanto, D., & Gani, B. A. (2022) · Dental and Medical Problems · doi:10.17219/dmp/142760 · Cited by 18

Selective effects of a short transient environmental fluctuation on a natural population

Pfenninger, M., Foucault, Q., Waldvogel, A., & Feldmeyer, B. (2022) · Molecular Ecology · doi:10.1111/mec.16748 · Cited by 18

A tool for RNA sequencing sample identity check

Huang, J., Chen, J., Lathrop, M. G., & Liang, L. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt155 · Cited by 19

Proteomic Studies Related to Genetic Determinants of Variability in Protein Concentrations

Horvatovich, P. L., Franke, L., & Bischoff, R. (2013) · Journal of Proteome Research · doi:10.1021/pr400765y · Cited by 18

Analyzing the Meiotic Transcriptome Using Isolated Meiocytes of Arabidopsis thaliana

Chen, C., & Retzel, E. F. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-333-6_20 · Cited by 18

Comparative study of population genomic approaches for mapping colony-level traits

Inbar, S., Cohen, P., Yahav, T., & Privman, E. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007653 · Cited by 18

Plant secondary metabolites

Filippis, L. F. D. (2015) · Wiley eBooks · doi:10.1002/9781119081005.ch15 · Cited by 17

Single-cell eQTL mapping reveals cell-type-specific genes associated with the risk of gastric cancer

Bian, L., Hu, B., Li, F., Gu, Y., Hu, C., Chen, Y., Deng, B., Fang, H., Zhu, X., Chen, Y., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100812 · Cited by 17

Resolving the Variable Genome and Epigenome in Human Disease

Knight, J. C. (2012) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2011.02508.x · Cited by 15

Mapping of hepatic expression quantitative trait loci (eQTLs) in a Han Chinese population

Wang, X., Tang, H., Teng, M., Li, Z., Li, J., Fan, J., Zhong, L., Sun, X., Xu, J., Chen, G., et al. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2013-102045 · Cited by 17

Single Nucleotide Variants in Transcription Factors Associate More Tightly with Phenotype than with Gene Expression

Sudarsanam, P., & Cohen, B. A. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004325 · Cited by 16

eQTL analysis links inflammatory bowel disease associated 1q21 locus to ECM1 gene

Repnik, K., & Potočnik, U. (2016) · Journal of Applied Genetics · doi:10.1007/s13353-015-0334-1 · Cited by 14

A comprehensive review of the analysis and integration of omics data for SARS-CoV-2 and COVID-19

Zhu, Z., Zhang, S., Wang, P., Chen, X., Bi, J., Cheng, L., & Zhang, X. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab446 · Cited by 14

Liver expression quantitative trait loci: a foundation for pharmacogenomic research

Glubb, D. M., Dholakia, N., & Innocenti, F. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00153 · Cited by 14

Multi-omics analysis for identifying cell-type-specific and bulk-level druggable targets in Alzheimer’s disease

Liu, S., Cho, M., Huang, Y.-N., Park, T., Chaudhuri, S., Rosewood, T. J., Bice, P. J., Chung, D., Bennett, D. A., Ertekin‐Taner, N., et al. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-06739-1 · Cited by 17

Response of the Salmon Heart Transcriptome to Pancreas Disease: Differences Between High- and Low-Ranking Families for Resistance

Robinson, N. A., Krasnov, A., Burgerhout, E., Johnsen, H., Moghadam, H. K., Hillestad, B., Aslam, M. L., Baranski, M., & Boison, S. A. (2020) · Scientific Reports · doi:10.1038/s41598-020-57786-1 · Cited by 13

Whole Transcriptome Profiling: An RNA‐Seq Primer and Implications for Pharmacogenomics Research

Sá, A. C. C., Sadée, W., & Johnson, J. A. (2017) · Clinical and Translational Science · doi:10.1111/cts.12511 · Cited by 14

Transcriptome changes in apple peel tissues during CO2 injury symptom development under controlled atmosphere storage regimens

Johnson, F., & Zhu, Y. (2015) · Horticulture Research · doi:10.1038/hortres.2015.61 · Cited by 12

Model based heritability scores for high-throughput sequencing data

Rudra, P., Shi, W. J., Vestal, B. E., Russell, P. H., Odell, A. T., Dowell, R. D., Radcliffe, R. A., Saba, L. M., & Kechris, K. J. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1539-6 · Cited by 13

Integrated Genomics Approaches in Evolutionary and Ecological Endocrinology

Kitano, J., Ishikawa, A., & Lema, S. C. (2013) · Advances in experimental medicine and biology · doi:10.1007/978-94-007-7347-9_15 · Cited by 12

ulfasQTL: an ultra-fast method of composite splicing QTL analysis

Yang, Q., Hu, Y., Li, J., & Zhang, X. (2017) · BMC Genomics · doi:10.1186/s12864-016-3258-1 · Cited by 11

Mapping gene-environment interactions at regulatory polymorphisms: Insights into mechanisms of phenotypic variation

Maranville, J., Luca, F., Stephens, M., & Rienzo, A. D. (2012) · Transcription · doi:10.4161/trns.19497 · Cited by 13

Molecular and physiological characterization of grapevine rootstock adaptation to drought

Peccoux, A. (2011) · Oskar-Bordeaux (Universite de Bordeaux) · Cited by 11

In silico Analysis of Polymorphisms in microRNAs Deregulated in Alzheimer Disease

Moraghebi, M., Maleki, R., Ahmadi, M., Negahi, A. A., Abbasi, H., & Mousavi, P. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.631852 · Cited by 10

An integrative approach to prioritize candidate causal genes for complex traits in cattle

Ghoreishifar, S. M., MacLeod, I. M., Chamberlain, A. J., Liu, Z., Lopdell, T., Littlejohn, M. D., Xiang, R., Pryce, J. E., & Goddard, M. E. (2025) · PLoS Genetics · doi:10.1371/journal.pgen.1011492 · Cited by 9

Exon expression QTL (eeQTL) analysis highlights distant genomic variations associated with splicing regulation

Guan, L., Yang, Q., Gu, M., Chen, L., & Zhang, X. (2014) · Quantitative Biology · doi:10.1007/s40484-014-0031-9 · Cited by 9

Three-Dimensional Morphometrics for Quantitative Trait Locus Analysis: Tackling Complex Questions with Complex Phenotypes

Jamniczky, H. A., Campeau, S., Barry, T. N., Skelton, J., & Rogers, S. M. (2015) · Evolutionary Biology · doi:10.1007/s11692-015-9318-7 · Cited by 9

New Technologies to Study Functional Genomics of Age-Related Macular Degeneration

Nguyen, T., Urrutia-Cabrera, D., Liou, R. H.-C., Luu, C. D., Guymer, R. H., & Wong, R. C. B. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.604220 · Cited by 9

Inference of Allele-Specific Expression from RNA-seq Data

Korir, P. K., & Seoighe, C. (2014) · Methods in molecular biology · doi:10.1007/978-1-62703-773-0_4 · Cited by 9

A spectral framework to map QTLs affecting joint differential networks of gene co-expression

Hu, J., Weber, J. N., Fuess, L. E., Steinel, N. C., Bolnick, D. I., & Wang, M. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012953 · Cited by 8

A map of cis-regulatory modules and constituent transcription factor binding sites in 80% of the mouse genome

Ni, P., Wilson, D., & Su, Z. (2022) · BMC Genomics · doi:10.1186/s12864-022-08933-7 · Cited by 7

eRNA co-expression network uncovers TF dependency and convergent cooperativity

Lee, S. A., Kristjánsdóttir, K., & Kwak, H. (2023) · Scientific Reports · doi:10.1038/s41598-023-46415-2 · Cited by 6

SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies

Gorlov, I. P., Xiao, X., Mayes, M. D., Gorlova, O. Y., & Amos, C. I. (2019) · BMC Genetics · doi:10.1186/s12863-019-0786-0 · Cited by 8

Gene expression in large pedigrees: analytic approaches

Cantor, R. M., & Cordell, H. J. (2016) · BMC Genetics · doi:10.1186/s12863-015-0311-z · Cited by 7

Transcriptome Sequencing (RNA-Seq)

Reuther, J., Roy, A., & Monzon, F. A. (2018) · Springer eBooks · doi:10.1007/978-3-319-96830-8_4 · Cited by 7

DNA methylome and transcriptome profiling reveal key electrophysiology and immune dysregulation in hypertrophic cardiomyopathy

Li, X., Fan, H., Song, X., Song, B., Liu, W., Dong, R., Zhang, H., Guo, S., Liang, H., Schrodi, S. J., et al. (2023) · Epigenetics · doi:10.1080/15592294.2023.2195307 · Cited by 7

Interpreting noncoding genetic variation in complex traits and human disease

Ward, L. D., & Kellis, M. (2012) · Nature Biotechnology · doi:10.1038/nbt.2422 · Cited by 6

SPATS2L is a positive feedback regulator of the type I interferon signaling pathway and plays a vital role in lupus

Chen, M., Zhang, Y., Shi, W., Song, X., Yang, Y., Hou, G., Ding, H., Chen, S., Yang, W., Shen, N., et al. (2024) · Acta Biochimica et Biophysica Sinica · doi:10.3724/abbs.2024132 · Cited by 4

Cis-regulatory variation: significance in biomedicine and evolution

Friedensohn, S., & Sawarkar, R. (2014) · Cell and Tissue Research · doi:10.1007/s00441-014-1855-3 · Cited by 6

Minireview: Genome Editing of Human Pluripotent Stem Cells for Modeling Metabolic Disease

Yu, H., & Cowan, C. A. (2016) · Molecular Endocrinology · doi:10.1210/me.2015-1290 · Cited by 6

Bioenergy Trees: Genetic and Genomic Strategies to Improve Yield

Taylor, G., Allwright, M., Smith, H. K., Polle, A., Wildhagen, H., Hertzberg, M., Bhalerao, R. P., Keurentjes, J. J. B., Scalabrin, S., Scaglione, D., et al. (2016) · Springer eBooks · doi:10.1007/978-3-319-44530-4_15 · Cited by 6

Comprehensive Cis-Regulation Analysis of Genetic Variants in Human Lymphoblastoid Cell Lines

Wang, Y., He, B., Zhao, Y., Reiter, J. L., Chen, S., Simpson, E. R., Feng, W., & Liu, Y. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00806 · Cited by 5

Schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk: A mediation analysis

Peng, X., Bader, J. S., & Avramopoulos, D. (2021) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32841 · Cited by 6

Gene expression in African Americans and Latinos reveals ancestry-specific patterns of genetic architecturePreprint

Kachuri, L., Mak, A. C. Y., Hu, D., Eng, C. S., Huntsman, S., Elhawary, J. R., Gupta, N., Gabriel, S., Xiao, S., Keys, K. L., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.19.456901 · Cited by 6

Efficiently Identifying Significant Associations in Genome-Wide Association Studies

Kostem, E., & Eskin, E. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37195-0_10 · Cited by 5

A functional schizophrenia-associated genetic variant near the TSNARE1 and ADGRB1 genes

Wahbeh, M. H., Boyd, R. J., Yovo, C., Rike, B., McCallion, A. S., & Avramopoulos, D. (2024) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2024.100303 · Cited by 5

Allele-specific binding variants causing ChIP-seq peak height of histone modification are not enriched in expression QTL annotations

Ghoreishifar, S. M., Chamberlain, A. J., Xiang, R., Prowse-Wilkins, C., Lopdell, T., Littlejohn, M. D., Pryce, J. E., & Goddard, M. E. (2024) · Genetics Selection Evolution · doi:10.1186/s12711-024-00916-4 · Cited by 5

dcVar: a method for identifying common variants that modulate differential correlation structures in gene expression data

Lareau, C. A., White, B. C., Montgomery, C. G., & McKinney, B. A. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00312 · Cited by 5

Global Approaches to Alternative Splicing and Its Regulation—Recent Advances and Open Questions

Hsiao, Y.-H. E., Cass, A. A., Bahn, J. H., Lin, X., & Xiao, X. G. (2015) · Translational bioinformatics · doi:10.1007/978-94-017-7450-5_2 · Cited by 5

Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data

Farkas, C., Fuentes‐Villalobos, F., Rebolledo‐Jaramillo, B., Benavides, F. J., Castro, A. F., & Pincheira, R. (2019) · BMC Genomics · doi:10.1186/s12864-019-5504-9 · Cited by 5

Human variation in population-wide gene expression data predicts gene perturbation phenotype

Bonaguro, L., Schulte-Schrepping, J., Carraro, C., Sun, L. L., Reiz, B., Gemünd, I. D., Saglam, A., Rahmouni, S., Georges, M., Arts, P., et al. (2022) · iScience · doi:10.1016/j.isci.2022.105328 · Cited by 5

Allele specific binding of histone modifications and a transcription factor does not predict allele specific expression in correlated ChIP-seq peak-exon pairs

Prowse-Wilkins, C., Wang, J., Garner, J. B., Goddard, M. E., & Chamberlain, A. J. (2023) · Scientific Reports · doi:10.1038/s41598-023-42637-6 · Cited by 5

Functional Genomics Research in Aquaculture: Principles and General Approaches

Liu, S., Zhang, Y., Sun, F., Jiang, Y., Wang, R., Li, C., Zhang, J., & Liu, Z. (2012) · Wiley eBooks · doi:10.1002/9781118350041.ch1 · Cited by 5

eQTL analysis: A bridge from genome to mechanism

Jia, Z., Xu, J., Ma, Y., Wei, S., Sun, C., Chen, X., Kang, J., Chen, H., Zhang, C., Dong, Y., et al. (2025) · Genes & Diseases · doi:10.1016/j.gendis.2025.101850 · Cited by 5

Transcriptome Sequencing (RNA-Seq)

Daniel, S., Paniz‐Mondolfi, A., & Monzon, F. A. (2014) · Springer eBooks · doi:10.1007/978-1-4939-0727-4_3 · Cited by 4

Analysis Considerations for Utilizing RNA-Seq to Characterize the Brain Transcriptome

ZHENG, C. L., Kawane, S., Bottomly, D., & Wilmot, B. (2014) · International review of neurobiology · doi:10.1016/b978-0-12-801105-8.00002-3 · Cited by 4

Efficiently Identifying Significant Associations in Genome-wide Association Studies

Kostem, E., & Eskin, E. (2013) · Journal of Computational Biology · doi:10.1089/cmb.2013.0087 · Cited by 4

Identification of cis-regulatory variations in the IL6R gene through the inheritance assessment of allelic transcription

Oh, S. A., Byun, H., Jang, E.-S., & Jeong, S. (2013) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2013.10.029 · Cited by 4

Genetics of Atherosclerotic Cardiovascular Disease

Qasim, A., & Reilly, M. P. (2013) · Elsevier eBooks · doi:10.1016/b978-0-12-383834-6.00061-6 · Cited by 4

LSCC SNP variant regulates SOX2 modulation of VDAC3

Chyr, J., Guo, D., & Zhou, X. (2018) · Oncotarget · doi:10.18632/oncotarget.24918 · Cited by 3

QTL Mapping of Molecular Traits for Studies of Human Complex Diseases

Liu, C. (2012) · Translational bioinformatics · doi:10.1007/978-94-007-5558-1_5 · Cited by 3

Advances in Genome Science

Joosen, R. V. L., Ligterink, W., Hilhorst, H. W. M., & Keurentjes, J. J. B. (2013) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/97816080575661130201 · Cited by 3

The Promise of eQTL Studies in Dissecting Crop Genetic Basis and Evolution

Fu, J., Leng, P., Wang, G., & Zhao, J. Y. (2022) · Wiley eBooks · doi:10.1002/9781119312994.apr0775 · Cited by 3

QTL Mapping of Molecular Traits for Studies of Human Complex Diseases

Liu, C. (2018) · Translational bioinformatics · doi:10.1007/978-981-13-1071-3_6 · Cited by 1

Disease Risk Assessment Using a Voronoi-Based Network Analysis of Genes and Variants Scores

Chen, L., Mukerjee, G., Dorfman, R., & Moghadas, S. M. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00029 · Cited by 2

BRCA1 VUS: A functional analysis to differentiate pathogenic from benign variants identified in clinical diagnostic panels for breast cancer

Lourenço, R., Lança, M. B., Gil, O. M., Cardoso, J., Lourenço, T., Pereira‐Leal, J. B., Rodrigues, A. S., Rueff, J., & Silva, S. (2023) · Molecular Medicine Reports · doi:10.3892/mmr.2023.13023 · Cited by 2

Liver Expression Quantitative Trait Loci (eQTL) and Related Approaches in Pharmacogenomic Studies

Glubb, D. M., Etheridge, A. S., Seiser, E., & Innocenti, F. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-386882-4.00007-4 · Cited by 2

Principles and Implications of Various Genome Enrichment Approaches for Targeted Sequencing of Plant Genomes

Kaur, P., & Gaikwad, K. (2019) · Springer eBooks · doi:10.1007/978-981-13-8499-8_2 · Cited by 2

RNA sequencing for the study of gene expression regulation

Gonçalves, Â. (2012) · Apollo (University of Cambridge) · doi:10.17863/cam.11726 · Cited by 2

eQTL Analysis Elucidates the Genetic Basis Underlying Transgressive Gene Expression in Nelumbo Hybrids

Gao, Z., Xiao, Y., Chen, J., & Shi, T. (2025) · Molecular Ecology · doi:10.1111/mec.70203 · Cited by 1

Transcriptional and Linkage Analyses Identify Loci that Mediate the Differential Macrophage Response to Inflammatory Stimuli and Infection

Hassan, M. A., Jensen, K. D. C., Butty, V. L., Hu, K. H., Boedec, E., Prins, P., & Saeij, J. P. J. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005619 · Cited by 2

Combining Genetic and Developmental Methods to Study Musculoskeletal Evolution in Primates

Capellini, T. D., & Dingwall, H. L. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316388907.009 · Cited by 1

Gene Expression Studies and Complex Diseases

Göring, H. H. H. (2015) · Springer eBooks · doi:10.1007/978-3-662-46306-2_5 · Cited by 2

Basics of immunogenetics: application and future perspectives

Hajam, Y. A., Kumar, R., Bhat, R. A., Rani, R., Sharma, B., & Sharma, P. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-90053-9.00001-4 · Cited by 1

Transforming Diagnosis and Therapeutics Using Cancer Genomics

Mehmood, S., Aslam, S., Dilshad, E., Ismail, H., & Khan, A. N. (2023) · Cancer treatment and research · doi:10.1007/978-3-031-27156-4_2 · Cited by 1

Mapping Expression Quantitative Trait Loci Targeting Candidate Genes for Pregnancy in Beef Cows

Diniz, W. J. S., Afonso, J., Kertz, N. C., Dyce, P. W., & Banerjee, P. (2024) · Biomolecules · doi:10.3390/biom14020150 · Cited by 2

Genetics and Genomics of Atherosclerotic Cardiovascular Disease

Musunuru, K., Qasim, A., & Reilly, M. P. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-812532-8.00007-0 · Cited by 2

Genomics, Genetics, and Breeding in Aquaculture

Maluwa, A. O. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-824296-4.00003-7 · Cited by 1

Molecular Basis of Complex Traits

Polychronakos, C. (2011) · Wiley eBooks · doi:10.1002/9780470015902.a0021448 · Cited by 1

Complex polymorphic genetic architecture underlies trans -regulatory variation among strains of Saccharomyces cerevisiaePreprint

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