  Mapping gene expression as a quantitative trait using whole genome-sequencing
and transcriptome analysis allows to discover the functional consequences of
genetic variation. We developed a novel method and ultra-fast software Findr
for higly accurate causal inference between gene expression traits using
cis-regulatory DNA variations as causal anchors, which improves current methods
by taking into account hidden confounders and weak regulations. Findr
outperformed existing methods on the DREAM5 Systems Genetics challenge and on
the prediction of microRNA and transcription factor targets in human
lymphoblastoid cells, while being nearly a million times faster. Findr is
publicly available at https://github.com/lingfeiwang/findr

Genomics;Molecular Networks;Quantitative Methods