Mapping complex disease traits with global gene expression

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

Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities

Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,633

A General Framework for Weighted Gene Co-Expression Network Analysis

Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684

Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease

Hugot, J.-P., Chamaillard, M., Zouali, H., Lesage, S., Cézard, J.-P., Belaiche, J., Almer, S., Tysk, C., O'Morain, C. A., Gassull, M., et al. (2001) · Nature · doi:10.1038/35079107 · Cited by 5,591

The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease

Lamb, J., Crawford, E. D., Peck, D., Modell, J. W., Blat, I. C., Wrobel, M. J., Lerner, J., Brunet, J.-P., Subramanian, A., Ross, K. N., et al. (2006) · Science · doi:10.1126/science.1132939 · Cited by 5,257

The human disease network

Goh, K.-I., Cusick, M. E., Valle, D., Childs, B., Vidal, M., & Barabási, A.-L. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0701361104 · Cited by 3,242

Common loss-of-function variants of the epidermal barrier protein filaggrin are a major predisposing factor for atopic dermatitis

Palmer, C. N. A., Irvine, A. D., Terron-Kwiatkowski, A., Zhao, Y., Liao, H., Lee, S. P., Goudie, D. R., Sandilands, A., Campbell, L. E., Smith, F. J. D., et al. (2006) · Nature Genetics · doi:10.1038/ng1767 · Cited by 2,978

Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease

the NIDDK IBD Genetics Consortium, Barrett, J. C., the Belgian-French IBD Consortium, the Wellcome Trust Case Control Consortium, Hansoul, S., Nicolae, D. L., Cho, J. H., Duerr, R. H., Rioux, J. D., Brant, S. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.175 · Cited by 2,593

Heritability in the genomics era — concepts and misconceptions

Visscher, P. M., Hill, W. G., & Wray, N. R. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2322 · Cited by 1,921

An Oncogene-Induced DNA Damage Model for Cancer Development

Halazonetis, T. D., Gorgoulis, V. G., & Bartek, J. (2008) · Science · doi:10.1126/science.1140735 · Cited by 1,851

Exon-Specific QTLs Skew the Inferred Distribution of Expression QTLs Detected Using Gene Expression Array Data

Veyrieras, J., Gaffney, D. J., Pickrell, J. K., Gilad, Y., Stephens, M., & Pritchard, J. K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030629 · Cited by 17

Transcriptomic Profiles of Monocyte-Derived Macrophages in Response to Escherichia coli is Associated with the Host Genetics

Emam, M., Cánovas, Á., Islas‐Trejo, A., Fonseca, P. A. D. S., Medrano, J. F. F., & Mallard, B. A. (2020) · Scientific Reports · doi:10.1038/s41598-019-57089-0 · Cited by 17

Targeting the lysine-specific demethylase 1 rewires kinase networks and primes leukemia cells for kinase inhibitor treatment

Pedicona, F., Casado, P., Hijazi, M., Gribben, J. G., Rouault‐Pierre, K., & Cutillas, P. R. (2022) · Science Signaling · doi:10.1126/scisignal.abl7989 · Cited by 17

Evolutionary history of regulatory variation in human populations

Lappalainen, T., & Dermitzakis, E. T. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq406 · Cited by 19

Discovering Single Nucleotide Polymorphisms Regulating Human Gene Expression Using Allele Specific Expression from RNA-seq Data

Kang, E. Y., Martin, L. J., Mangul, S., Isvilanonda, W., Zou, J., Ben‐David, E., Han, B., Lusis, A. J., Shifman, S., & Eskin, E. (2016) · Genetics · doi:10.1534/genetics.115.177246 · Cited by 19

Predicting links between tumor samples and genes using 2-Layered graph based diffusion approach

Timilsina, M., Yang, H., Sahay, R., & Rebholz‐Schuhmann, D. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3056-2 · Cited by 17

Exploring the genetic basis of diseases through a heterogeneous bibliometric network: A methodology and case study

Wu, M., Zhang, Y., Zhang, G., & Lü, J. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120513 · Cited by 18

Genomic architecture of sickle cell disease in West African children

Quinlan, J., Idaghdour, Y., Goulet, J.-P., Gbeha, E., de Malliard, T., Bruat, V., Grenier, J., Gomez, S., Sanni, A., Rahimy, M. C., et al. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00026 · Cited by 17

High-Performance Mixed Models Based Genome-Wide Association Analysis with omicABEL software

Fabregat‐Traver, D., Sharapov, S., Hayward, C., Rudan, I., Campbell, H. J., Aulchenko, Y. S., & Bientinesi, P. (2014) · F1000Research · doi:10.12688/f1000research.4867.1 · Cited by 17

Functional characterisation of the osteoarthritis susceptibility locus at chromosome 6q14.1 marked by the polymorphism rs9350591

Johnson, K., Reynard, L. N., & Loughlin, J. A. (2015) · BMC Medical Genetics · doi:10.1186/s12881-015-0215-9 · Cited by 17

Transcriptomic signatures for human male infertility

Hodžić, A., Maver, A., Zorn, B., Petrovič, D., Kunej, T., & Peterlin, B. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1226829 · Cited by 17

Detection of cis-acting regulatory SNPs using allelic expression data

Xiao, R., & Scott, L. J. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20601 · Cited by 16

Lessons and Implications from Genome-Wide Association Studies (GWAS) Findings of Blood Cell Phenotypes

Chami, N., & Lettre, G. (2014) · Genes · doi:10.3390/genes5010051 · Cited by 16

A distance-based test of association between paired heterogeneous genomic data

Minas, C., Curry, E. W., & Montana, G. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt450 · Cited by 16

A Systems Biology Approach for Identifying Novel Pathway Regulators in eQTL Mapping

Li, S., Lu, Q. L., & Cui, Y. (2010) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543400903572803 · Cited by 16

Epigenome editing of the CFTR-locus for treatment of cystic fibrosis

Kabadi, A. M., Machlin, L., Dalal, N., Lee, R. E., McDowell, I. C., Shah, N. N., Drowley, L., Randell, S. H., & Reddy, T. E. (2021) · Journal of Cystic Fibrosis · doi:10.1016/j.jcf.2021.04.008 · Cited by 17

Causal Gene Identification Using Non-Linear Regression-Based Independence Tests

Zhang, H., Yan, C., Xia, Y., Guan, J., & Zhou, S. (2022) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3149864 · Cited by 16

Deciphering the molecular basis of venous thromboembolism: where are we and where should we go?

Morange, P., & Trégouët, D. (2009) · British Journal of Haematology · doi:10.1111/j.1365-2141.2009.07975.x · Cited by 18

The age of the “ome”: Genome, transcriptome and proteome data set collection and analysis

Myers, A. (2011) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2011.11.015 · Cited by 16

From an ACE polymorphism to genome-wide searches for eQTL

Soubrier, F. (2013) · Journal of Clinical Investigation · doi:10.1172/jci66618 · Cited by 16

Omic personality: implications of stable transcript and methylation profiles for personalized medicine

Tabassum, R., Sivadas, A., Agrawal, V., Tian, H., Arafat, D., & Gibson, G. C. (2015) · Genome Medicine · doi:10.1186/s13073-015-0209-4 · Cited by 16

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

Ju, J. H., Shenoy, S. A., Crystal, R. G., & Mezey, J. G. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005537 · Cited by 17

eQTL mapping identifies insertion- and deletion-specific eQTLs in multiple tissues

Huang, J., Chen, J., Esparza, J., Ding, J., Elder, J. T., Abecasis, G. R., Lee, Y.-A., Lathrop, M. G., Moffatt, M. F., Cookson, W., et al. (2015) · Nature Communications · doi:10.1038/ncomms7821 · Cited by 16

Deep Learning Enables Fast and Accurate Imputation of Gene Expression

Viñas, R., Azevedo, T., Gamazon, E. R., & Lió, P. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.624128 · Cited by 16

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

Proceedings: Consideration of Genetics in the Design of Induced Pluripotent Stem Cell-Based Models of Complex Disease

Grieshammer, U., & Shepard, K. A. (2014) · Stem Cells Translational Medicine · doi:10.5966/sctm.2014-0191 · Cited by 15

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

Next-generation DNA sequencing-based assay for measuring allelic expression imbalance (AEI) of candidate neuropsychiatric disorder genes in human brain

Xu, X. H., Wang, H., Zhu, M., Sun, Y., Yu, T., He, Q., Wang, J., Chen, L., & Saffen, D. W. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-518 · Cited by 15

Gene expression variations: potentialities of master regulator polymorphisms in colorectal cancer risk

Pardini, B., Naccarati, A., Vodička, P., & Kumar, R. (2012) · Mutagenesis · doi:10.1093/mutage/ger057 · Cited by 15

Design of Split Proximity Circuit as a Plug-and-Play Translator for Point Mutation Discrimination

Ang, Y. S., Lai, P. S., & Yung, L. L. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c01379 · Cited by 15

A multigenotype maize silk expression atlas reveals how exposure‐related stresses are mitigated following emergence from husk leaves

McNinch, C., Chen, K., Dennison, T., Lopez, M. D., Yandeau‐Nelson, M. D., & Lauter, N. (2020) · The Plant Genome · doi:10.1002/tpg2.20040 · Cited by 15

Microarray Evidences the Role of Pathologic Adipose Tissue in Insulin Resistance and Their Clinical Implications

Mathur, S. K., Jain, P., & Mathur, P. (2011) · Journal of Obesity · doi:10.1155/2011/587495 · Cited by 15

Alternative Approaches in Gene Discovery and Characterization in Alzheimer’s Disease

Ertekin‐Taner, N., Jager, P. L. D., Yu, L., & Bennett, D. A. (2013) · Current Genetic Medicine Reports · doi:10.1007/s40142-013-0007-5 · Cited by 16

A vascular endothelial growth factor receptor gene variant is associated with susceptibility to acute respiratory distress syndrome

the GEN-SEP Network, Hernandez‐Pacheco, N., Guillén‐Guío, B., Acosta‐Herrera, M., Pino-Yanes, M. D. M., Corrales, A., Ambrós, A., Nogales, L., Muriel, A., González-Higueras, E., et al. (2018) · Intensive Care Medicine Experimental · doi:10.1186/s40635-018-0181-6 · Cited by 15

IGREX for quantifying the impact of genetically regulated expression on phenotypes

Cai, M., Chen, L., Liu, J., & Yang, C. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa010 · Cited by 15

Genome-wide mapping of regulatory variants for temperature- and salinity-adaptive genes reveals genetic basis of genotype-by-environment interaction in Crassostrea ariakensis

Zhang, K., Yang, Q., Du, M., Zhang, Z., Wang, W., Zhang, G., Li, A., & Li, L. (2023) · Environmental Research · doi:10.1016/j.envres.2023.116614 · Cited by 14

Path from schizophrenia genomics to biology: gene regulation and perturbation in neurons derived from induced pluripotent stem cells and genome editing

Duan, J. (2015) · Neuroscience Bulletin · doi:10.1007/s12264-014-1488-2 · Cited by 14

Inference of modules associated to eQTLs

Kreimer, A., Litvin, O., Hao, K., Molony, C. M., Pe’er, D., & Pe'er, I. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks269 · Cited by 14

Detecting Genetic Associations betweenATG5and Lupus Nephritis bytrans-eQTL

Zhang, Y., Cheng, F., Zhou, S., Qi, Y., Hou, P., Zhao, M., & Zhang, H. (2015) · Journal of Immunology Research · doi:10.1155/2015/153132 · Cited by 14

Accurate eQTL prioritization with an ensemble‐based framework

Zeng, H., Edwards, M. D., Guo, Y., & Gifford, D. K. (2017) · Human Mutation · doi:10.1002/humu.23198 · Cited by 14

Complex Networks Approach for Analyzing the Correlation of Traditional Chinese Medicine Syndrome Evolvement and Cardiovascular Events in Patients with Stable Coronary Heart Disease

Gao, Z., Li, S., Shang, Q., Jiao, Y., Zhou, X., Fu, C., Xu, H., Shi, D., & Chen, K. (2015) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2015/824850 · Cited by 14

Targeted isolation of cloned genomic regions by recombineering for haplotype phasing and isogenic targeting

Nedelkova, M., Maresca, M., Fu, J., Rostovskaya, M., Chenna, R., Thiede, C., Anastassiadis, K., Sarov, M., & Stewart, A. F. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr668 · Cited by 14

Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility

Piccolo, S., Andrulis, I. L., Cohen, A. L., Conner, T. A., Moos, P. J., Spira, A. E., Buys, S. S., Johnson, W. E., & Bild, A. H. (2015) · BMC Medical Genomics · doi:10.1186/s12920-015-0145-6 · Cited by 14

The 3D genome: From fundamental principles to disease and cancer

Umlauf, D., & Mourad, R. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.07.002 · Cited by 15

Linking Variants From Genome-Wide Association Analysis to Function via Transcriptional Network Analysis

Keller, B. J., Martini, S., Sedor, J. R., & Kretzler, M. (2010) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2010.01.008 · Cited by 14

Expression Quantitative Trait Loci (eQTL) Mapping in Puerto Rican Children

Chen, W., Brehm, J. M., Lin, J., Wang, T., Forno, E., Acosta‐Pérez, E., Boutaoui, N., CANINO, G. J., & Celedon, J. C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122464 · Cited by 13

Identification of Potential Causal Genes for Neurodegenerative Diseases by Mitochondria-Related Genome-Wide Mendelian Randomization

Yin, K., Chen, T., Gu, X., Jiang, Z., Su, W., Duan, Q., Wen, X.-J., Cao, B., Li, J.-R., Chi, L., et al. (2024) · Molecular Neurobiology · doi:10.1007/s12035-024-04528-3 · Cited by 13

Teamwork: Improved eQTL Mapping Using Combinations of Machine Learning Methods

Ackermann, M., Clément‐Ziza, M., Michaelson, J. J., & Beyer, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040916 · Cited by 13

High-resolution analysis of cis -acting regulatory networks at the α-globin locus

Hughes, J. R., Lower, K. M., Dunham, I., Taylor, S., Gobbi, M. D., Sloane-Stanley, J. A., McGowan, S. J., Ragoussis, J., Vernimmen, D., Gibbons, R. J., et al. (2013) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0361 · Cited by 13

How can genetics and epigenetics help the nephrologist improve the diagnosis and treatment of chronic kidney disease patients?

Witasp, A., Ekström, T. J., Schalling, M., Lindholm, B., Stenvinkel, P., & Nordfors, L. (2014) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfu021 · Cited by 14

Application of quantitative metabolomics in systems genetics in rodent models of complex phenotypes

Gauguier, D. (2015) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2015.09.016 · Cited by 14

Exploiting expression patterns across multiple tissues to map expression quantitative trait loci

Acharya, C. R., McCarthy, J., Owzar, K., & Allen, A. S. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1123-5 · Cited by 13

Identification of expression quantitative trait loci (eQTLs) in human peripheral blood mononuclear cells (PBMCs) and shared with liver and brain

He, P., Xia, W., Wang, L., Wu, J. H., Guo, Y., Zeng, K., Wang, M., Bing, P., Xie, F., Lu, X., et al. (2017) · Journal of Cellular Biochemistry · doi:10.1002/jcb.26325 · Cited by 13

A Common Haplotype of the TNF Receptor 2 Gene Modulates Endotoxin Tolerance

Fairfax, B. P., Davenport, E. E., Makino, S., Hill, A. V. S., Vannberg, F. O., & Knight, J. C. (2011) · The Journal of Immunology · doi:10.4049/jimmunol.1001791 · Cited by 13

RNA expression in human retina

Li, M., Zauhar, R. J., Grazal, C. F., Curcio, C. A., DeAngelis, M. M., & Stambolian, D. E. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx219 · Cited by 13

The association between vitamin D receptor polymorphisms and tissue-specific insulin resistance in human obesity

Pramono, A., Jocken, J. W. E., Adriaens, M. E., Hjorth, M. F., Astrup, A. V., Saris, W. H. M., & Blaak, E. E. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00744-2 · Cited by 13

LPS-induced modules of co-expressed genes in equine peripheral blood mononuclear cells

Pacholewska, A., Marti, E., Leeb, T., Jagannathan, V., & Gerber, V. (2017) · BMC Genomics · doi:10.1186/s12864-016-3390-y · Cited by 15

Integrative analyses reveal signaling pathways underlying familial breast cancer susceptibility

Piccolo, S., Hoffman, L. M., Conner, T. A., Shrestha, G., Cohen, A. L., Marks, J. R., Neumayer, L. A., Agarwal, C., Beckerle, M. C., Andrulis, I. L., et al. (2016) · Molecular Systems Biology · doi:10.15252/msb.20156506 · Cited by 13

Genetic aspects of schizophrenia

Morozova, A. Y., Zubkov, E. A., Zorkina, Y., Reznik, A. M., Kostyuk, G. P., & Chekhonin, V. P. (2017) · S S Korsakov Journal of Neurology and Psychiatry · doi:10.17116/jnevro201711761126-132 · Cited by 12

Urban–rural differences in the gene expression profiles of Ghanaian children

Amoah, A. S., Obeng, B. B., May, L., Kruize, Y. C. M., Larbi, I. A., Kabesch, M., Wilson, ⁄., Hartgers, F. C., Boakye, D. A., & Yazdanbakhsh, M. (2014) · Genes and Immunity · doi:10.1038/gene.2014.21 · Cited by 13

PS4DR: a multimodal workflow for identification and prioritization of drugs based on pathway signatures

Emon, M. A., Domingo‐Fernándéz, D., Hoyt, C. T., & Hofmann‐Apitius, M. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03568-5 · Cited by 12

Genetics and the general physician: insights, applications and future challenges

Knight, J. C. (2009) · QJM · doi:10.1093/qjmed/hcp115 · Cited by 12

Molecular Quantitative Trait Locus Mapping in Human Complex Diseases

Olayinka, O. A., O’Neill, N. K., Farrer, L. A., Wang, G., & Zhang, X. (2022) · Current Protocols · doi:10.1002/cpz1.426 · Cited by 11

Trends in Precision Medicine

Kaur, J., Rahat, B., Thakur, S., & Kaur, J. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809411-2.00015-5 · Cited by 14

Efficient and effective control of confounding in eQTL mapping studies through joint differential expression and Mendelian randomization analyses

Fan, Y., Zhu, H., Song, Y., Peng, Q., & Zhou, X. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa715 · Cited by 11

Dominant complementation of biological pathways in maize hybrid lines is associated with heterosis

Zhou, T., Afzal, R., Haroon, M., Ma, Y., Zhang, H., & Li, L. (2022) · Planta · doi:10.1007/s00425-022-04028-5 · Cited by 11

Single‐Cell Transcriptomics of Bone Marrow Stromal Cells in Diversity Outbred Mice: A Model for Population‐Level scRNA ‐Seq Studies

Dillard, L. J., Rosenow, W. T., Calabrese, G. M., Mesner, L. D., Al-Barghouthi, B. M., Abood, A., Farber, E., Önengüt-Gümüşcü, S., Tommasini, S. M., Horowitz, M. A., et al. (2023) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.4882 · Cited by 11

Comparing Computational Methods for Identification of Allele‐Specific Expression based on Next Generation Sequencing Data

Liu, Z., Yang, J., Xu, H., Li, C., Wang, Z., Li, Y., Dong, X., & Li, Y. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21846 · Cited by 11

Towards a comprehensive picture of the genetic landscape of complex traits

Wang, Z., Wang, Y., Wang, N., Wang, J., Wang, Z., Vallejos, C. E., & Wu, R. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs049 · Cited by 11

Insights from GWAS into the quantitative genetics of transcription in humans

Kim, J., & Gibson, G. C. (2010) · Genetics Research · doi:10.1017/s001667231000056x · Cited by 11

Association analyses of eQTLs of the TYRO3 gene and allergic diseases in Japanese populations

Kanazawa, J., Masuko, H., Yatagai, Y., Sakamoto, T., Yamada, H., Kitazawa, H., Iijima, H., Naito, T., Saito, T., Noguchi, E., et al. (2018) · Allergology International · doi:10.1016/j.alit.2018.07.004 · Cited by 11

Making Biological Sense of Genetic Studies of Age-Related Macular Degeneration

Singh, N., Swaroop, A., & Ratnapriya, R. (2021) · Advances in Experimental Medicine and Biology · doi:10.1007/978-3-030-66014-7_8 · Cited by 11

Modeling expression quantitative trait loci in data combining ethnic populations

Hsiao, C.-L., Lian, I., Hsieh, A., & Fann, C. S. J. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-111 · Cited by 11

Genetic variation in interleukin-7 is associated with a reduced erythropoietic response in Kenyan children infected with Plasmodium falciparum

Kisia, L. E., Kempaiah, P., Anyona, S. B., Munde, E. O., Achieng, A. O., Ong’echa, J. M., Lambert, C. G., Chelimo, K., Ouma, C., Perkins, D. J., et al. (2019) · BMC Medical Genetics · doi:10.1186/s12881-019-0866-z · Cited by 11

Optimizing Gene Expression Analysis Using Clustering Algorithms

Bikku, T., Ramu, J., Sekhar, J. C., Pratap, V. K., & Pujari, J. J. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-99-9707-7_15 · Cited by 10

Statistical and Machine Learning Methods for eQTL Analysis

Chen, J., & Nodzak, C. (2019) · Methods in molecular biology · doi:10.1007/978-1-0716-0026-9_7 · Cited by 10

regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data

Xu, S., Feng, W., Lu, Z., Yu, C. Y., Shao, W., Nakshatri, H., Reiter, J. L., Gao, H., Chu, X., Wang, Y., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00886 · Cited by 10

Cell type–specific eQTLs in the human immune system

Gregersen, P. K. (2012) · Nature Genetics · doi:10.1038/ng.2258 · Cited by 10

VNN1 Gene Expression Levels and the G-137T Polymorphism Are Associated with HDL-C Levels in Mexican Prepubertal Children

Jacobo‐Albavera, L., la Rosa, P. I. A.-D., Villarreal-Molina, M. T., Villamil‐Ramírez, H., León‐Mimila, P., Romero‐Hidalgo, S., López-Contreras, B. E., Sánchez‐Muñoz, F., Bojalil, R., González-Barrios, J. A., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0049818 · Cited by 10

Allelic expression analysis of the osteoarthritis susceptibility locus that maps to MICAL3

Ratnayake, M., Reynard, L. N., Raine, E. V. A., Santibanez‐Koref, M., & Loughlin, J. A. (2012) · BMC Medical Genetics · doi:10.1186/1471-2350-13-12 · Cited by 10

What Will Diabetes Genomes Tell Us?

Mohlke, K. L., & Scott, L. J. (2012) · Current Diabetes Reports · doi:10.1007/s11892-012-0321-4 · Cited by 10

Applying genome-wide gene-based expression quantitative trait locus mapping to study population ancestry and pharmacogenetics

Yang, H., Lin, C., Chen, C., & Chen, J. J. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-319 · Cited by 10

Methods for optimizing statistical analyses in pharmacogenomics research

Turner, S., Crawford, D. C., & Ritchie, M. D. (2009) · Expert Review of Clinical Pharmacology · doi:10.1586/ecp.09.32 · Cited by 10

The search for susceptibility genes in lumbar disc degeneration : focus on young individuals

Eskola, P. J. (2012) · Cited by 9

Contribution of coding/non-coding variants in NUS1 to late-onset sporadic Parkinson's disease

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Functional annotation of breast cancer risk loci: current progress and future directions

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