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Results: 1 to 20 of 91

Similar articles for PubMed (Select 22492648)

1.

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.

2.

Expression quantitative trait loci analysis identifies associations between genotype and gene expression in human intestine.

Kabakchiev B, Silverberg MS.

Gastroenterology. 2013 Jun;144(7):1488-96, 1496.e1-3. doi: 10.1053/j.gastro.2013.03.001. Epub 2013 Mar 6.

3.

Genome-wide co-expression analysis in multiple tissues.

Grieve IC, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J.

PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.

4.

FastMap: fast eQTL mapping in homozygous populations.

Gatti DM, Shabalin AA, Lam TC, Wright FA, Rusyn I, Nobel AB.

Bioinformatics. 2009 Feb 15;25(4):482-9. doi: 10.1093/bioinformatics/btn648. Epub 2008 Dec 17.

5.

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.

6.

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.

7.

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.

8.

A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies.

Stegle O, Parts L, Durbin R, Winn J.

PLoS Comput Biol. 2010 May 6;6(5):e1000770. doi: 10.1371/journal.pcbi.1000770.

9.

An information-theoretic machine learning approach to expression QTL analysis.

Huang T, Cai YD.

PLoS One. 2013 Jun 25;8(6):e67899. doi: 10.1371/journal.pone.0067899. Print 2013.

10.

SNPexp - A web tool for calculating and visualizing correlation between HapMap genotypes and gene expression levels.

Holm K, Melum E, Franke A, Karlsen TH.

BMC Bioinformatics. 2010 Dec 17;11:600. doi: 10.1186/1471-2105-11-600.

11.

An integrated hierarchical Bayesian model for multivariate eQTL mapping.

Scott-Boyer MP, Imholte GC, Tayeb A, Labbe A, Deschepper CF, Gottardo R.

Stat Appl Genet Mol Biol. 2012 Jul 12;11(4). pii: /j/sagmb.2012.11.issue-4/1544-6115.1760/1544-6115.1760.xml. doi: 10.1515/1544-6115.1760.

PMID:
22850063
12.

Expression quantitative trait loci analysis of genes in porcine muscle by quantitative real-time RT-PCR compared to microarray data.

Ponsuksili S, Murani E, Phatsara C, Schwerin M, Schellander K, Wimmers K.

Heredity (Edinb). 2010 Sep;105(3):309-17. doi: 10.1038/hdy.2010.5. Epub 2010 Feb 10.

13.

Mapping quantitative trait loci for expression abundance.

Jia Z, Xu S.

Genetics. 2007 May;176(1):611-23. Epub 2007 Mar 4.

14.

Single nucleotide polymorphisms affect both cis- and trans-eQTLs.

Chen L, Page GP, Mehta T, Feng R, Cui X.

Genomics. 2009 Jun;93(6):501-8. doi: 10.1016/j.ygeno.2009.01.011. Epub 2009 Feb 25.

15.

Methodological aspects of the genetic dissection of gene expression.

Carlborg O, De Koning DJ, Manly KF, Chesler E, Williams RW, Haley CS.

Bioinformatics. 2005 May 15;21(10):2383-93.

16.

Association and expression quantitative trait loci (eQTL) analysis of porcine AMBP, GC and PPP1R3B genes with meat quality traits.

Cinar MU, Kayan A, Uddin MJ, Jonas E, Tesfaye D, Phatsara C, Ponsuksili S, Wimmers K, Tholen E, Looft C, Jüngst H, Schellander K.

Mol Biol Rep. 2012 Apr;39(4):4809-21. doi: 10.1007/s11033-011-1274-4. Epub 2011 Sep 27.

PMID:
21947951
17.

iBMQ: a R/Bioconductor package for integrated Bayesian modeling of eQTL data.

Imholte GC, Scott-Boyer MP, Labbe A, Deschepper CF, Gottardo R.

Bioinformatics. 2013 Nov 1;29(21):2797-8. doi: 10.1093/bioinformatics/btt485. Epub 2013 Aug 19.

18.

Learning gene networks under SNP perturbations using eQTL datasets.

Zhang L, Kim S.

PLoS Comput Biol. 2014 Feb 27;10(2):e1003420. doi: 10.1371/journal.pcbi.1003420. eCollection 2014 Feb. Erratum in: PLoS Comput Biol. 2014 Apr;10(4):e1003608.

19.

Identification of single nucleotide polymorphisms regulating peripheral blood mRNA expression with genome-wide significance: an eQTL study in the Japanese population.

Sasayama D, Hori H, Nakamura S, Miyata R, Teraishi T, Hattori K, Ota M, Yamamoto N, Higuchi T, Amano N, Kunugi H.

PLoS One. 2013;8(1):e54967. doi: 10.1371/journal.pone.0054967. Epub 2013 Jan 24.

20.

REVEAL--visual eQTL analytics.

Jäger G, Battke F, Nieselt K.

Bioinformatics. 2012 Sep 15;28(18):i542-i548. doi: 10.1093/bioinformatics/bts382.

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