CellMapper: Rapid and Accurate Inference of Gene Expression in Difficult-to-isolate Cell Types

Authors

Bradlee D. Nelms, Harvard University
Levi Waldron, CUNY School of Public HealthFollow
Luis A. Barrera, Harvard University
Andrew W. Weflen, Harvard University
Jeremy A. Goettel, Harvard University
Guoji Guo, Zhejiang University
Robert K. Montgomery, Harvard University
Marian R. Neutra, Harvard University
David T. Breault, Harvard University
Scott B. Snapper, Harvard University
Stuart H. Orkin, Harvard University
Martha L. Bulyk, Harvard University
Curtis Huttenhower, Harvard University
Wayne I. Lencer, Harvard University

Document Type

Article

Publication Date

2016

Abstract

We present a sensitive approach to predict genes expressed selectively in specific cell types, by searching publicly available expression data for genes with a similar expression profile to known cell-specific markers. Our method, CellMapper, strongly outperforms previous computational algorithms to predict cell type-specific expression, especially for rare and difficult-to-isolate cell types. Furthermore, CellMapper makes accurate predictions for human brain cell types that have never been isolated, and can be rapidly applied to diverse cell types from many tissues. We demonstrate a clinically relevant application to prioritize candidate genes in disease susceptibility loci identified by GWAS.

Comments

This article was originally published in Genome Biology, available at DOI 10.1186/s13059-016-1062-5.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License.