eQTL resources from the Gilad/Pritchard group


Resources regarding gene regulation from the Pritchard lab and Gilad lab. :

  1. [iPSC vQTLs] Download data from our paper on understanding the impact of genetic variation on variance of gene expression across cells.

  2. [IPSCs] Download data from our paper on understanding cell type-specific effects of DNA variation and on characterizing the suitability of induced pluripotent stem cells (iPSCs) as models for studies of complex disease.

  3. [RNA splicing] Download data from our paper on understanding the links between variation in the major steps of gene regulation and complex traits.

  4. [Histone modification and Pol2 data] Download data from 4 histone modifications (H3K4me1, H3K4me3, H3K27ac, H3K27me3) and and RNA Pol2 from 10 YRI lymphoblastoid cell lines.

  5. [MNase-seq data] Download MNase-seq data from 7 YRI lymphoblastoid cell lines. [Gaffney, McVicker et al. (2012)]

  6. [DNase-seq data] Download DNase-seq data from 70 YRI lymphoblastoid cell lines. [Degner, Pai, Pique-Regi et al. (2012)] or browse dsQTL results on our QTL browser

  7. [Transcription Factor binding sites] Download positions of transcription factor binding sites inferred in the HapMap lymphoblastoid cell lines by CENTIPEDE. [Pique-Regi, Degner et al. (2011); see link for further description]

  8. [RNA-Seq Data] Download raw and mapped RNA-Seq data from Pickrell et al. (2010).

  1. [RNA-Seq Software] Assorted scripts for identifying sequencing reads covering genes, polyadenylation sites and exon-exon junctions. [Pickrell et al. (2010) Nature and Pickrell et al. (2010) PLoS Gen]

  1. [Methylation Data] Download data and meQTL results for Illumina27K methylation data in HapMap lymphoblastoid cell lines. [Bell et al. (2011)]

  1. [Genome masking files] Download files to mask out areas of the genome that are prone to causing false positives in ChIP-seq and other sequencing based functional assays [Pickrell et al. (submitted)]

  1. [eQTL Browser] Browse eQTLs identified in recent studies in multiple tissues. The browser is based on code developed by the Generic Model Organism Database project, and was put together and is maintained by Jacob Degner and Jordana Bell with help from Joseph Pickrell. Instructions for use are available here.

Image from Veyrieras et al. (2008)

References [* - denotes equal contribution]:

J. Degner*, A. Pai*, R. Pique-Regi*, J.B. Veyrieras, D. Gaffney, J. Pickrell, S. De Leon, K. Michelini, N. Lewellen, G. Crawford M. Stephens, Y. Gilad, and J. Pritchard. DNaseI sensitivity QTLs are a major determinant of human expression variation. Nature. 2012 Feb 5; [early access]

Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, Gilad Y, Pritchard JK. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 2011 Jan 20;12(1):R10. [pubmed]

Pique-Regi R*, Degner JF*, Pai AA, Gaffney DJ, Gilad Y, Pritchard JK. Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data. Genome Research. 2011. Jan 20. [pubmed]

Pickrell JK, Pai AA, Gilad Y, Pritchard JK. Noisy splicing drives mRNA isoform diversity in human cells. PLoS Genetics. 2010. Dec 9;6(12):e1001236. [pubmed]

Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, Nkadori E,  Veyrieras J-B, Stephens M, Gilad Y, Pritchard JK. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature. 2010. Apr 1;464(7289):768-72. [pubmed] [slidecast]

Degner JF, Marioni JC, Pai AA, Pickrell JK, Nkadori E, Gilad Y, Pritchard JK. Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data. Bioinformatics. 2009. Dec 15;25(24):3207-12. [pubmed]

Veyrieras JB, Kudaravalli S, Kim SY, Dermitzakis ET, Gilad Y, Stephens M, Pritchard JK. High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genetics. 2008 Oct;4(10):e1000214. [pubmed]