Pathway-Level Information ExtractoR (PLIER) for gene expression data

A major challenge in gene expression analysis is to accurately infer relevant biological insight, such as variation in cell type proportion or pathway activity, from global gene expression studies. We present a general solution for this problem that outperforms available cell proportion inference al...

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Detalles Bibliográficos
Autores principales: Mao, Weiguang, Zaslavsky, Elena, Hartmann, Boris M., Sealfon, Stuart C., Chikina, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262669/
https://www.ncbi.nlm.nih.gov/pubmed/31249421
http://dx.doi.org/10.1038/s41592-019-0456-1
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author Mao, Weiguang
Zaslavsky, Elena
Hartmann, Boris M.
Sealfon, Stuart C.
Chikina, Maria
author_facet Mao, Weiguang
Zaslavsky, Elena
Hartmann, Boris M.
Sealfon, Stuart C.
Chikina, Maria
author_sort Mao, Weiguang
collection PubMed
description A major challenge in gene expression analysis is to accurately infer relevant biological insight, such as variation in cell type proportion or pathway activity, from global gene expression studies. We present a general solution for this problem that outperforms available cell proportion inference algorithms, and is more widely useful to automatically identify specific pathways that regulate gene expression. Our method improves replicability and biological insight when applied to trans-eQTL identification.
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spelling pubmed-72626692020-06-01 Pathway-Level Information ExtractoR (PLIER) for gene expression data Mao, Weiguang Zaslavsky, Elena Hartmann, Boris M. Sealfon, Stuart C. Chikina, Maria Nat Methods Article A major challenge in gene expression analysis is to accurately infer relevant biological insight, such as variation in cell type proportion or pathway activity, from global gene expression studies. We present a general solution for this problem that outperforms available cell proportion inference algorithms, and is more widely useful to automatically identify specific pathways that regulate gene expression. Our method improves replicability and biological insight when applied to trans-eQTL identification. 2019-06-27 2019-07 /pmc/articles/PMC7262669/ /pubmed/31249421 http://dx.doi.org/10.1038/s41592-019-0456-1 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Mao, Weiguang
Zaslavsky, Elena
Hartmann, Boris M.
Sealfon, Stuart C.
Chikina, Maria
Pathway-Level Information ExtractoR (PLIER) for gene expression data
title Pathway-Level Information ExtractoR (PLIER) for gene expression data
title_full Pathway-Level Information ExtractoR (PLIER) for gene expression data
title_fullStr Pathway-Level Information ExtractoR (PLIER) for gene expression data
title_full_unstemmed Pathway-Level Information ExtractoR (PLIER) for gene expression data
title_short Pathway-Level Information ExtractoR (PLIER) for gene expression data
title_sort pathway-level information extractor (plier) for gene expression data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262669/
https://www.ncbi.nlm.nih.gov/pubmed/31249421
http://dx.doi.org/10.1038/s41592-019-0456-1
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AT sealfonstuartc pathwaylevelinformationextractorplierforgeneexpressiondata
AT chikinamaria pathwaylevelinformationextractorplierforgeneexpressiondata

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