Data for "RNA splicing is a primary link between genetic variation and disease"

This webpage provides data for our paper on understanding the links between variation in the major steps of gene regulation and complex traits:

Li YI, van de Geijn B, Raj A, Knowles DA, Petti AA, Golan David, Gilad Y, Pritchard JK. "RNA splicing is a primary link between genetic variation and disease". Science. 2016.

Raw Data

The 4sU-seq data generated by this study are available for download from GEO under accession GSE75220.

Processed Data

A subset of the input files we used to run linear regression after WASP processing are here (includes qqnormed data and YRI genotypes):

processed (WASP+normalized) 4sU-seq (30m)

processed (WASP+normalized) 4sU-seq (60m)

processed (WASP+normalized) RNA-seq (Pickrell)

processed (WASP+normalized) RNA-seq (GEUVADIS)

processed (WASP+normalized) ribo-seq

processed (WASP+normalized) H3K27ac ChIP-seq

processed (WASP+normalized) intron splicing (see LeafCutter)

A subset of the input files we used to run linear regression from previous studies:

from (Pai et al., 2012) RNA decay

LifOver from (Banovich et al., 2013) DNA methylation

LiftOver from (Battle et al., 2015) protein

Summary stats:

splicing QTLs (matrixQTL)

expression QTLs (GEUVADIS) (matrixQTL)

combined (4su, RNAseq, ribo, prot) phenotypes pvalue:beta:ste

YRI genotypes used:

genotypes of 120 YRI individuals

Source Code

Source code for LeafCutter, our novel sQTL mapping method is available here. The manuscript describing LeafCutter has been posted on biorXiv.

Contact

For questions please contact: Yang I Li (yangili@stanford.edu), Yoav Gilad (gilad@uchicago.edu), or Jonathan Pritchard (pritch@stanford.edu).


Last updated 15/5/2016.