OUTRIDER: A Statistical Method for Detecting Aberrantly Expressed Genes in RNA Sequencing Data

RNA sequencing (RNA-seq) is gaining popularity as a complementary assay to genome sequencing for precisely identifying the molecular causes of rare disorders. A powerful approach is to identify aberrant gene expression levels as potential pathogenic events. However, existing methods for detecting aberrant read counts in RNA-seq data either lack assessments of statistical significance, so that establishing cutoffs is arbitrary, or rely on subjective manual corrections for confounders. Here, we describe OUTRIDER (Outlier in RNA-Seq Finder), an algorithm developed to address these issues.

Source: The American Journal of Human Genetics - November 29, 2018 Category: Genetics & Stem Cells Authors: Felix Brechtmann, Christian Mertes, Agn ė Matusevičiūtė, Vicente A. Yépez, Žiga Avsec, Maximilian Herzog, Daniel M. Bader, Holger Prokisch, Julien Gagneur Tags: Article Source Type: research