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Validation of Immune Cell Modules in Multicellular Transcriptomic Data
Numerous gene signatures, or modules have been described to evaluate the immune cell composition in transcriptomes of multicellular tissue samples. However, significant diversity in module gene content for specific cell types is associated with heterogeneity in their performance. In order to rank mo...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5207692/ https://www.ncbi.nlm.nih.gov/pubmed/28045996 http://dx.doi.org/10.1371/journal.pone.0169271 |
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author | Pollara, Gabriele Murray, Matthew J. Heather, James M. Byng-Maddick, Rachel Guppy, Naomi Ellis, Matthew Turner, Carolin T. Chain, Benjamin M. Noursadeghi, Mahdad |
author_facet | Pollara, Gabriele Murray, Matthew J. Heather, James M. Byng-Maddick, Rachel Guppy, Naomi Ellis, Matthew Turner, Carolin T. Chain, Benjamin M. Noursadeghi, Mahdad |
author_sort | Pollara, Gabriele |
collection | PubMed |
description | Numerous gene signatures, or modules have been described to evaluate the immune cell composition in transcriptomes of multicellular tissue samples. However, significant diversity in module gene content for specific cell types is associated with heterogeneity in their performance. In order to rank modules that best reflect their purported association, we have generated the modular discrimination index (MDI) score that assesses expression of each module in the target cell type relative to other cells. We demonstrate that MDI scores predict modules that best reflect independently validated differences in cellular composition, and correlate with the covariance between cell numbers and module expression in human blood and tissue samples. Our analyses demonstrate that MDI scores provide an ordinal summary statistic that reliably ranks the accuracy of gene expression modules for deconvolution of cell type abundance in transcriptional data. |
format | Online Article Text |
id | pubmed-5207692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-52076922017-01-19 Validation of Immune Cell Modules in Multicellular Transcriptomic Data Pollara, Gabriele Murray, Matthew J. Heather, James M. Byng-Maddick, Rachel Guppy, Naomi Ellis, Matthew Turner, Carolin T. Chain, Benjamin M. Noursadeghi, Mahdad PLoS One Research Article Numerous gene signatures, or modules have been described to evaluate the immune cell composition in transcriptomes of multicellular tissue samples. However, significant diversity in module gene content for specific cell types is associated with heterogeneity in their performance. In order to rank modules that best reflect their purported association, we have generated the modular discrimination index (MDI) score that assesses expression of each module in the target cell type relative to other cells. We demonstrate that MDI scores predict modules that best reflect independently validated differences in cellular composition, and correlate with the covariance between cell numbers and module expression in human blood and tissue samples. Our analyses demonstrate that MDI scores provide an ordinal summary statistic that reliably ranks the accuracy of gene expression modules for deconvolution of cell type abundance in transcriptional data. Public Library of Science 2017-01-03 /pmc/articles/PMC5207692/ /pubmed/28045996 http://dx.doi.org/10.1371/journal.pone.0169271 Text en © 2017 Pollara et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pollara, Gabriele Murray, Matthew J. Heather, James M. Byng-Maddick, Rachel Guppy, Naomi Ellis, Matthew Turner, Carolin T. Chain, Benjamin M. Noursadeghi, Mahdad Validation of Immune Cell Modules in Multicellular Transcriptomic Data |
title | Validation of Immune Cell Modules in Multicellular Transcriptomic Data |
title_full | Validation of Immune Cell Modules in Multicellular Transcriptomic Data |
title_fullStr | Validation of Immune Cell Modules in Multicellular Transcriptomic Data |
title_full_unstemmed | Validation of Immune Cell Modules in Multicellular Transcriptomic Data |
title_short | Validation of Immune Cell Modules in Multicellular Transcriptomic Data |
title_sort | validation of immune cell modules in multicellular transcriptomic data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5207692/ https://www.ncbi.nlm.nih.gov/pubmed/28045996 http://dx.doi.org/10.1371/journal.pone.0169271 |
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