{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T15:37:10Z","timestamp":1770910630482,"version":"3.50.1"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Identification of expression Quantitative Trait Loci (eQTL), the genetic loci that contribute to heritable variation in gene expression, can be obstructed by factors that produce variation in expression profiles if these factors are unmeasured or hidden from direct analysis.<\/jats:p>\n               <jats:p>Methods: We have developed a method for Hidden Expression Factor analysis (HEFT) that identifies individual and pleiotropic effects of eQTL in the presence of hidden factors. The HEFT model is a combined multivariate regression and factor analysis, where the complete likelihood of the model is used to derive a ridge estimator for simultaneous factor learning and detection of eQTL. HEFT requires no pre-estimation of hidden factor effects; it provides P-values and is extremely fast, requiring just a few hours to complete an eQTL analysis of thousands of expression variables when analyzing hundreds of thousands of single nucleotide polymorphisms on a standard 8 core 2.6 G desktop.<\/jats:p>\n               <jats:p>Results: By analyzing simulated data, we demonstrate that HEFT can correct for an unknown number of hidden factors and significantly outperforms all related hidden factor methods for eQTL analysis when there are eQTL with univariate and multivariate (pleiotropic) effects. To demonstrate a real-world application, we applied HEFT to identify eQTL affecting gene expression in the human lung for a study that included presumptive hidden factors. HEFT identified all of the cis-eQTL found by other hidden factor methods and 91 additional cis-eQTL. HEFT also identified a number of eQTLs with direct relevance to lung disease that could not be found without a hidden factor analysis, including cis-eQTL for GTF2H1 and MTRR, genes that have been independently associated with lung cancer.<\/jats:p>\n               <jats:p>Availability: Software is available at http:\/\/mezeylab.cb.bscb.cornell.edu\/Software.aspx.<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <jats:p>Contact: \u00a0jgm45@cornell.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt690","type":"journal-article","created":{"date-parts":[[2013,12,5]],"date-time":"2013-12-05T02:39:46Z","timestamp":1386211186000},"page":"369-376","source":"Crossref","is-referenced-by-count":19,"title":["HEFT: eQTL analysis of many thousands of expressed genes while simultaneously controlling for hidden factors"],"prefix":"10.1093","volume":"30","author":[{"given":"Chuan","family":"Gao","sequence":"first","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicole L.","family":"Tignor","sequence":"additional","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacqueline","family":"Salit","sequence":"additional","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yael","family":"Strulovici-Barel","sequence":"additional","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil R.","family":"Hackett","sequence":"additional","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronald G.","family":"Crystal","sequence":"additional","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason G.","family":"Mezey","sequence":"additional","affiliation":[{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"},{"name":"1 Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA and 2Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,12,4]]},"reference":[{"key":"2023012710413684900_btt690-B1","first-page":"1042","article-title":"xQTL workbench: a scalable web environment for multi-level QTL analysis","volume":"28","author":"Arends","year":"2012","journal-title":"Bioinformatics (Oxford, England)"},{"key":"2023012710413684900_btt690-B2","doi-asserted-by":"crossref","first-page":"1294","DOI":"10.1093\/bioinformatics\/btm108","article-title":"GenABEL: an R library for genome-wide association analysis","volume":"23","author":"Aulchenko","year":"2007","journal-title":"Bioinformatics (Oxford, England)"},{"key":"2023012710413684900_btt690-B3","doi-asserted-by":"crossref","first-page":"1044","DOI":"10.1101\/gr.088773.108","article-title":"Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver","volume":"19","author":"Brunner","year":"2009","journal-title":"Genome Res."},{"key":"2023012710413684900_btt690-B4","volume-title":"Transformation and Weighting in Regression (Chapman and Hall\/CRC Monographs on Statistics and Applied Probability)","author":"Carroll","year":"1988","edition":"1 edn"},{"key":"2023012710413684900_btt690-B5","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1101\/gr.083634.108","article-title":"Fast and flexible simulation of DNA sequence data","volume":"19","author":"Chen","year":"2009","journal-title":"Genome Res."},{"key":"2023012710413684900_btt690-B6","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1038\/nrg2630","article-title":"Genetics of human gene expression: mapping DNA variants that influence gene expression","volume":"10","author":"Cheung","year":"2009","journal-title":"Nat. Rev. Genet."},{"key":"2023012710413684900_btt690-B7","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1038\/nrg2537","article-title":"Mapping complex disease traits with global gene expression","volume":"10","author":"Cookson","year":"2009","journal-title":"Nat. Rev. Genet"},{"key":"2023012710413684900_btt690-B8","doi-asserted-by":"crossref","first-page":"e175","DOI":"10.1093\/nar\/gni179","article-title":"Evolving gene\/transcript definitions significantly alter the interpretation of geneChip data","volume":"33","author":"Dai","year":"2005","journal-title":"Nucleic Acids Res."},{"key":"2023012710413684900_btt690-B9","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.lungcan.2006.12.010","article-title":"Chromosomal aberrations and gene expression profiles in non-small cell lung cancer","volume":"56","author":"Dehan","year":"2007","journal-title":"Lung Cancer (Amsterdam, Netherlands)"},{"key":"2023012710413684900_btt690-B10","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1038\/nature10808","article-title":"DNase 1 sensitivity QTLs are a major determinant of human expression variation","volume":"482","author":"Denger","year":"2012","journal-title":"Nature"},{"key":"2023012710413684900_btt690-B11","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1111\/j.0006-341X.1999.00997.x","article-title":"Genomic control for association studies","volume":"55","author":"Devlin","year":"1999","journal-title":"Biometrics"},{"key":"2023012710413684900_btt690-B12","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1093\/nar\/30.1.207","article-title":"Gene expression omnibus: NCBI gene expression and hybridization array data repository","volume":"30","author":"Edgar","year":"2002","journal-title":"Nucleic Acids Res."},{"key":"2023012710413684900_btt690-B13","doi-asserted-by":"crossref","first-page":"e1001117","DOI":"10.1371\/journal.pgen.1001117","article-title":"Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis","volume":"6","author":"Engelhardt","year":"2010","journal-title":"PLoS Genet."},{"key":"2023012710413684900_btt690-B14","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1198\/jasa.2009.tm08332","article-title":"A factor model approach to multiple testing under dependence","volume":"104","author":"Friguet","year":"2009","journal-title":"J. Am. Stat. Assoc."},{"key":"2023012710413684900_btt690-B15","doi-asserted-by":"crossref","first-page":"e1002330","DOI":"10.1371\/journal.pcbi.1002330","article-title":"Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies","volume":"8","author":"Fusi","year":"2012","journal-title":"PLoS Comput. Biol."},{"key":"2023012710413684900_btt690-B16","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/s00109-006-0103-z","article-title":"Modification of gene expression of the small airway epithelium in response to cigarette smoking","volume":"85","author":"Harvey","year":"2007","journal-title":"J. Mol. Med."},{"key":"2023012710413684900_btt690-B17","doi-asserted-by":"crossref","first-page":"1909","DOI":"10.1534\/genetics.108.094201","article-title":"Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots","volume":"180","author":"Kang","year":"2008","journal-title":"Genetics"},{"key":"2023012710413684900_btt690-B18","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1038\/ng.548","article-title":"Variance component model to account for sample structure in genome-wide association studies","volume":"42","author":"Kang","year":"2010","journal-title":"Nat. Genet."},{"key":"2023012710413684900_btt690-B19","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1093\/bioinformatics\/bts034","article-title":"The sva package for removing batch effects and other unwanted variation in high-throughput experiments","volume":"28","author":"Leek","year":"2012","journal-title":"Bioinformatics"},{"key":"2023012710413684900_btt690-B20","doi-asserted-by":"crossref","first-page":"e161","DOI":"10.1371\/journal.pgen.0030161","article-title":"Capturing heterogeneity in gene expression studies by surrogate variable analysis","volume":"3","author":"Leek","year":"2007","journal-title":"PLoS Genet."},{"key":"2023012710413684900_btt690-B21","doi-asserted-by":"crossref","first-page":"16465","DOI":"10.1073\/pnas.1002425107","article-title":"Correction for hidden confounders in the genetic analysis of gene expression","volume":"107","author":"Listgarten","year":"2010","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012710413684900_btt690-B22","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.ymeth.2009.03.004","article-title":"Detection and interpretation of expression quantitative trait loci (eQTL)","volume":"48","author":"Michaelson","year":"2009","journal-title":"Methods"},{"key":"2023012710413684900_btt690-B23","first-page":"4284","article-title":"TEFM (c17orf42) is necessary for transcription of human mtDNA","volume":"39","author":"Minczuk","year":"2011"},{"key":"2023012710413684900_btt690-B24","doi-asserted-by":"crossref","first-page":"R211","DOI":"10.1093\/hmg\/ddp400","article-title":"The resolution of the genetics of gene expression","volume":"18","author":"Montgomery","year":"2009","journal-title":"Hum. Mol. Genet."},{"key":"2023012710413684900_btt690-B25","doi-asserted-by":"crossref","first-page":"R129","DOI":"10.1093\/hmg\/ddn285","article-title":"Using gene expression to investigate the genetic basis of complex disorders","volume":"17","author":"Nica","year":"2008","journal-title":"Hum. Mol. Genet."},{"key":"2023012710413684900_btt690-B26","doi-asserted-by":"crossref","first-page":"e1001276","DOI":"10.1371\/journal.pgen.1001276","article-title":"Joint genetic analysis of gene expression data with inferred cellular phenotypes","volume":"7","author":"Parts","year":"2011","journal-title":"PLoS Genet."},{"key":"2023012710413684900_btt690-B27","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1038\/ng1847","article-title":"Principal components analysis corrects for stratification in genome-wide association studies","volume":"38","author":"Price","year":"2006","journal-title":"Nat. Genet."},{"key":"2023012710413684900_btt690-B28","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1186\/1471-2164-10-493","article-title":"Quality control in microarray assessment of gene expression in human airway epithelium","volume":"10","author":"Raman","year":"2009","journal-title":"BMC Genomics"},{"key":"2023012710413684900_btt690-B29","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1097\/01.fpc.0000170916.96650.70","article-title":"Polymorphisms of methionine synthase and methionine synthase reductase and risk of lung cancer: a case-control analysis","volume":"15","author":"Shi","year":"2005","journal-title":"Pharmacogenet. Genomics"},{"key":"2023012710413684900_btt690-B30","doi-asserted-by":"crossref","first-page":"e1000770","DOI":"10.1371\/journal.pcbi.1000770","article-title":"A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies","volume":"6","author":"Stegle","year":"2010","journal-title":"PLoS Comput. Biol."},{"key":"2023012710413684900_btt690-B31","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1038\/nprot.2011.457","article-title":"Using probabilistic estimation of expression residuals (peer) to obtain increased power and interpretability of gene expression analyses","volume":"7","author":"Stegle","year":"2012","journal-title":"Nat. Protoc."},{"key":"2023012710413684900_btt690-B32","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nrg2484","article-title":"RNA-seq: a revolutionary tool for transcriptomics","volume":"10","author":"Wang","year":"2009","journal-title":"Nat. Rev. Genet."},{"key":"2023012710413684900_btt690-B33","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.lungcan.2008.05.014","article-title":"Genetic variants in GTF2h1 and risk of lung cancer: a casecontrol analysis in a Chinese population","volume":"63","author":"Wu","year":"2009","journal-title":"Lung Cancer"},{"key":"2023012710413684900_btt690-B34","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1093\/bioinformatics\/btt075","article-title":"Accounting for non-genetic factors by low-rank representation and sparse regression for eQTL mapping","volume":"29","author":"Yang","year":"2013","journal-title":"Bioinformatics"},{"key":"2023012710413684900_btt690-B35","doi-asserted-by":"crossref","first-page":"e35762","DOI":"10.1371\/journal.pone.0035762","article-title":"Learning transcriptional regulatory relationships using sparse graphical models","volume":"7","author":"Zhang","year":"2012","journal-title":"PLoS One"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/3\/369\/48917344\/bioinformatics_30_3_369.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/3\/369\/48917344\/bioinformatics_30_3_369.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T10:55:48Z","timestamp":1674816948000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/30\/3\/369\/228688"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,12,4]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2014,2,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btt690","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2014,2,1]]},"published":{"date-parts":[[2013,12,4]]}}}