Validation of Immune Cell Modules in Multicellular Transcriptomic Data

被引:18
|
作者
Pollara, Gabriele [1 ]
Murray, Matthew J. [1 ]
Heather, James M. [1 ]
Byng-Maddick, Rachel [1 ]
Guppy, Naomi [2 ]
Ellis, Matthew [3 ]
Turner, Carolin T. [1 ]
Chain, Benjamin M. [1 ]
Noursadeghi, Mandad [1 ]
机构
[1] UCL, Div Infect & Immun, London, England
[2] UCL, UCL Adv Diagnost, London, England
[3] UCL, UCL Inst Neurol, Dept Neurodegenerat Dis, London, England
来源
PLOS ONE | 2017年 / 12卷 / 01期
基金
英国医学研究理事会; 英国生物技术与生命科学研究理事会; 英国惠康基金;
关键词
DELAYED-TYPE HYPERSENSITIVITY; SYSTEMIC-LUPUS-ERYTHEMATOSUS; ANALYSIS REVEALS; GENE-EXPRESSION; SIGNATURES; INFLAMMATION; POPULATIONS; ACTIVATION; COMPENDIUM; BIOLOGY;
D O I
10.1371/journal.pone.0169271
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:13
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