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CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5043525/ https://www.ncbi.nlm.nih.gov/pubmed/27687735 http://dx.doi.org/10.1186/s13059-016-1062-5 |
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author | Nelms, Bradlee D. Waldron, Levi Barrera, Luis A. Weflen, Andrew W. Goettel, Jeremy A. Guo, Guoji Montgomery, Robert K. Neutra, Marian R. Breault, David T. Snapper, Scott B. Orkin, Stuart H. Bulyk, Martha L. Huttenhower, Curtis Lencer, Wayne I. |
author_facet | Nelms, Bradlee D. Waldron, Levi Barrera, Luis A. Weflen, Andrew W. Goettel, Jeremy A. Guo, Guoji Montgomery, Robert K. Neutra, Marian R. Breault, David T. Snapper, Scott B. Orkin, Stuart H. Bulyk, Martha L. Huttenhower, Curtis Lencer, Wayne I. |
author_sort | Nelms, Bradlee D. |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1062-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5043525 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50435252016-10-05 CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types Nelms, Bradlee D. Waldron, Levi Barrera, Luis A. Weflen, Andrew W. Goettel, Jeremy A. Guo, Guoji Montgomery, Robert K. Neutra, Marian R. Breault, David T. Snapper, Scott B. Orkin, Stuart H. Bulyk, Martha L. Huttenhower, Curtis Lencer, Wayne I. Genome Biol Method 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1062-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-29 /pmc/articles/PMC5043525/ /pubmed/27687735 http://dx.doi.org/10.1186/s13059-016-1062-5 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Nelms, Bradlee D. Waldron, Levi Barrera, Luis A. Weflen, Andrew W. Goettel, Jeremy A. Guo, Guoji Montgomery, Robert K. Neutra, Marian R. Breault, David T. Snapper, Scott B. Orkin, Stuart H. Bulyk, Martha L. Huttenhower, Curtis Lencer, Wayne I. CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
title | CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
title_full | CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
title_fullStr | CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
title_full_unstemmed | CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
title_short | CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
title_sort | cellmapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5043525/ https://www.ncbi.nlm.nih.gov/pubmed/27687735 http://dx.doi.org/10.1186/s13059-016-1062-5 |
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