MaGIC: a machine learning tool set and web application for monoallelic gene inference from chromatin

Abstract

SummaryA large fraction of human and mouse autosomal genes are subject to random monoallelic expression (MAE), an epigenetic mechanism characterized by allele-specific gene expression that varies between clonal cell lineages. MAE is highly cell-type specific, and mapping it in a large number of cell and tissue types can provide insight into its biological function. Its detection, however, remains challenging. We previously reported that a sequence-independent chromatin signature identifies, with high sensitivity and specificity, genes subject to MAE in multiple tissue types using readily available ChIP-seq data. Here we present an implementation of this method as a user-friendly, open-source software pipeline for monoallelic gene inference from chromatin (MaGIC).\n\nAvailability and implementationThe source code for the MaGIC pipeline and the Shiny app is available at https://github.com/gimelbrantlab/magic.\n\nContactsebastien_vigneau@dfci.harvard.edu, gimelbrant@mail.dfci.harvard.edu