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Items: 1 to 20 of 100

1.

kruX: matrix-based non-parametric eQTL discovery.

Qi J, Asl HF, Björkegren J, Michoel T.

BMC Bioinformatics. 2014 Jan 14;15:11. doi: 10.1186/1471-2105-15-11.

2.

Nonparametric evaluation of quantitative traits in population-based association studies when the genetic model is unknown.

Konietschke F, Libiger O, Hothorn LA.

PLoS One. 2012;7(2):e31242. doi: 10.1371/journal.pone.0031242. Epub 2012 Feb 21.

3.

Matrix eQTL: ultra fast eQTL analysis via large matrix operations.

Shabalin AA.

Bioinformatics. 2012 May 15;28(10):1353-8. doi: 10.1093/bioinformatics/bts163. Epub 2012 Apr 6.

4.

Rapid and robust resampling-based multiple-testing correction with application in a genome-wide expression quantitative trait loci study.

Zhang X, Huang S, Sun W, Wang W.

Genetics. 2012 Apr;190(4):1511-20. doi: 10.1534/genetics.111.137737. Epub 2012 Jan 31.

5.

HT-eQTL: integrative expression quantitative trait loci analysis in a large number of human tissues.

Li G, Jima D, Wright FA, Nobel AB.

BMC Bioinformatics. 2018 Mar 9;19(1):95. doi: 10.1186/s12859-018-2088-3.

6.

QRank: a novel quantile regression tool for eQTL discovery.

Song X, Li G, Zhou Z, Wang X, Ionita-Laza I, Wei Y.

Bioinformatics. 2017 Jul 15;33(14):2123-2130. doi: 10.1093/bioinformatics/btx119.

7.

JEPEG: a summary statistics based tool for gene-level joint testing of functional variants.

Lee D, Williamson VS, Bigdeli TB, Riley BP, Fanous AH, Vladimirov VI, Bacanu SA.

Bioinformatics. 2015 Apr 15;31(8):1176-82. doi: 10.1093/bioinformatics/btu816. Epub 2014 Dec 12.

8.

Mapping eQTL by leveraging multiple tissues and DNA methylation.

Acharya CR, Owzar K, Allen AS.

BMC Bioinformatics. 2017 Oct 18;18(1):455. doi: 10.1186/s12859-017-1856-9.

9.

Comprehensively evaluating cis-regulatory variation in the human prostate transcriptome by using gene-level allele-specific expression.

Larson NB, McDonnell S, French AJ, Fogarty Z, Cheville J, Middha S, Riska S, Baheti S, Nair AA, Wang L, Schaid DJ, Thibodeau SN.

Am J Hum Genet. 2015 Jun 4;96(6):869-82. doi: 10.1016/j.ajhg.2015.04.015. Epub 2015 May 14.

10.

Haplotype-based quantitative trait mapping using a clustering algorithm.

Li J, Zhou Y, Elston RC.

BMC Bioinformatics. 2006 May 18;7:258.

11.

Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs.

Lee S, Xing EP.

Bioinformatics. 2012 Jun 15;28(12):i137-46. doi: 10.1093/bioinformatics/bts227.

12.

Simultaneous inferences based on empirical Bayes methods and false discovery rates ineQTL data analysis.

Chakraborty A, Jiang G, Boustani M, Liu Y, Skaar T, Li L.

BMC Genomics. 2013;14 Suppl 8:S8. doi: 10.1186/1471-2164-14-S8-S8. Epub 2013 Dec 9.

13.

Conditional entropy in variation-adjusted windows detects selection signatures associated with expression quantitative trait loci (eQTLs).

Handelman SK, Seweryn M, Smith RM, Hartmann K, Wang D, Pietrzak M, Johnson AD, Kloczkowski A, Sadee W.

BMC Genomics. 2015;16 Suppl 8:S8. doi: 10.1186/1471-2164-16-S8-S8. Epub 2015 Jun 18.

14.

Conditional eQTL analysis reveals allelic heterogeneity of gene expression.

Jansen R, Hottenga JJ, Nivard MG, Abdellaoui A, Laport B, de Geus EJ, Wright FA, Penninx BWJH, Boomsma DI.

Hum Mol Genet. 2017 Apr 15;26(8):1444-1451. doi: 10.1093/hmg/ddx043.

15.

Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution.

Beretta S, Castelli M, Gonçalves I, Kel I, Giansanti V, Merelli I.

J Comput Biol. 2018 Oct;25(10):1091-1105. doi: 10.1089/cmb.2017.0167. Epub 2018 Jul 27.

PMID:
30052049
16.

Identifying the genetic variation of gene expression using gene sets: application of novel gene Set eQTL approach to PharmGKB and KEGG.

Abo R, Jenkins GD, Wang L, Fridley BL.

PLoS One. 2012;7(8):e43301. doi: 10.1371/journal.pone.0043301. Epub 2012 Aug 14.

17.

Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs.

Brown CD, Mangravite LM, Engelhardt BE.

PLoS Genet. 2013;9(8):e1003649. doi: 10.1371/journal.pgen.1003649. Epub 2013 Aug 1.

18.

Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS.

Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ.

PLoS Genet. 2010 Apr 1;6(4):e1000888. doi: 10.1371/journal.pgen.1000888.

19.

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

Ju JH, Shenoy SA, Crystal RG, Mezey JG.

PLoS Comput Biol. 2017 May 15;13(5):e1005537. doi: 10.1371/journal.pcbi.1005537. eCollection 2017 May.

20.

Large-scale East-Asian eQTL mapping reveals novel candidate genes for LD mapping and the genomic landscape of transcriptional effects of sequence variants.

Narahara M, Higasa K, Nakamura S, Tabara Y, Kawaguchi T, Ishii M, Matsubara K, Matsuda F, Yamada R.

PLoS One. 2014 Jun 23;9(6):e100924. doi: 10.1371/journal.pone.0100924. eCollection 2014.

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