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

Vinogradova, S.; Saksena, S.; Ward, H.; Vigneau, S.; Gimelbrant, A.

doi:10.1101/353359

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bioRxiv · 10.1101/353359

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

Vinogradova, S.·Saksena, S.·Ward, H.·Vigneau, S.·Gimelbrant, A.

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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

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Vinogradova, S., Saksena, S., Ward, H., Vigneau, S., Gimelbrant, A.. 2018-06-22. MaGIC: a machine learning tool set and web application for monoallelic gene inference from chromatin. https://doi.org/10.1101/353359

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