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Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis
The transcriptional state of a cell reflects a variety of biological factors, from persistent cell-type specific features to transient processes such as cell cycle. Depending on biological context, all such aspects of transcriptional heterogeneity may be of interest, but detecting them from noisy si...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772672/ https://www.ncbi.nlm.nih.gov/pubmed/26780092 http://dx.doi.org/10.1038/nmeth.3734 |
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author | Fan, Jean Salathia, Neeraj Liu, Rui Kaeser, Gwendolyn E. Yung, Yun C. Herman, Joseph L. Kaper, Fiona Fan, Jian-Bing Zhang, Kun Chun, Jerold Kharchenko, Peter V. |
author_facet | Fan, Jean Salathia, Neeraj Liu, Rui Kaeser, Gwendolyn E. Yung, Yun C. Herman, Joseph L. Kaper, Fiona Fan, Jian-Bing Zhang, Kun Chun, Jerold Kharchenko, Peter V. |
author_sort | Fan, Jean |
collection | PubMed |
description | The transcriptional state of a cell reflects a variety of biological factors, from persistent cell-type specific features to transient processes such as cell cycle. Depending on biological context, all such aspects of transcriptional heterogeneity may be of interest, but detecting them from noisy single-cell RNA-seq data remains challenging. We developed PAGODA to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability amongst measured cells. |
format | Online Article Text |
id | pubmed-4772672 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
record_format | MEDLINE/PubMed |
spelling | pubmed-47726722016-07-18 Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis Fan, Jean Salathia, Neeraj Liu, Rui Kaeser, Gwendolyn E. Yung, Yun C. Herman, Joseph L. Kaper, Fiona Fan, Jian-Bing Zhang, Kun Chun, Jerold Kharchenko, Peter V. Nat Methods Article The transcriptional state of a cell reflects a variety of biological factors, from persistent cell-type specific features to transient processes such as cell cycle. Depending on biological context, all such aspects of transcriptional heterogeneity may be of interest, but detecting them from noisy single-cell RNA-seq data remains challenging. We developed PAGODA to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability amongst measured cells. 2016-01-18 2016-03 /pmc/articles/PMC4772672/ /pubmed/26780092 http://dx.doi.org/10.1038/nmeth.3734 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 Fan, Jean Salathia, Neeraj Liu, Rui Kaeser, Gwendolyn E. Yung, Yun C. Herman, Joseph L. Kaper, Fiona Fan, Jian-Bing Zhang, Kun Chun, Jerold Kharchenko, Peter V. Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
title | Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
title_full | Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
title_fullStr | Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
title_full_unstemmed | Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
title_short | Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
title_sort | characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772672/ https://www.ncbi.nlm.nih.gov/pubmed/26780092 http://dx.doi.org/10.1038/nmeth.3734 |
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