Validation of immune cell modules in multicellular transcriptomic data
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 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.
Cell Count, Gene Expression Profiling, Gene Expression Regulation, Humans, Leukocytes, Lymph Nodes, Reproducibility of Results, Skin, Transcriptome, Journal Article
1-13
Pollara, Gabriele
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Murray, Matthew J
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Heather, James M
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Byng-Maddick, Rachel
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Guppy, Naomi
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Ellis, Matthew
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Turner, Carolin T
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Chain, Benjamin M
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Noursadeghi, Mahdad
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2017
Pollara, Gabriele
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Murray, Matthew J
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Heather, James M
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Byng-Maddick, Rachel
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Guppy, Naomi
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Ellis, Matthew
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Turner, Carolin T
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Chain, Benjamin M
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Noursadeghi, Mahdad
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Pollara, Gabriele, Murray, Matthew J, Heather, James M, Byng-Maddick, Rachel, Guppy, Naomi, Ellis, Matthew, Turner, Carolin T, Chain, Benjamin M and Noursadeghi, Mahdad
(2017)
Validation of immune cell modules in multicellular transcriptomic data.
PLoS ONE, 12 (1), , [e0169271].
(doi:10.1371/journal.pone.0169271).
Abstract
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.
Text
journal.pone.0169271
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Accepted/In Press date: 14 December 2016
e-pub ahead of print date: 3 January 2017
Published date: 2017
Keywords:
Cell Count, Gene Expression Profiling, Gene Expression Regulation, Humans, Leukocytes, Lymph Nodes, Reproducibility of Results, Skin, Transcriptome, Journal Article
Identifiers
Local EPrints ID: 428134
URI: http://eprints.soton.ac.uk/id/eprint/428134
ISSN: 1932-6203
PURE UUID: 053cf0e9-dee7-4fe6-89af-5e4d234c7589
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Date deposited: 12 Feb 2019 17:30
Last modified: 16 Mar 2024 00:08
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Contributors
Author:
Gabriele Pollara
Author:
Matthew J Murray
Author:
James M Heather
Author:
Rachel Byng-Maddick
Author:
Naomi Guppy
Author:
Matthew Ellis
Author:
Carolin T Turner
Author:
Benjamin M Chain
Author:
Mahdad Noursadeghi
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