Best practices on the differential expression analysis of multi-species RNA-seq

被引：58

作者：

Chung, Matthew ^{[1
,2
]}

Bruno, Vincent M. ^{[1
,2
]}

Rasko, David A. ^{[1
,2
]}

Cuomo, Christina A. ^{[3
]}

Munoz, Jose F. ^{[3
]}

Livny, Jonathan ^{[3
]}

Shetty, Amol C. ^{[1
]}

Mahurkar, Anup ^{[1
]}

Dunning Hotopp, Julie C. ^{[1
,2
,4
]}

机构：

[1] Univ Maryland Sch Med, Inst Genome Sci, Baltimore, MD 21201 USA

[2] Univ Maryland Sch Med, Dept Microbiol & Immunol, Baltimore, MD 21201 USA

[3] Broad Inst, Infect Dis & Microbiome Program, Cambridge, MA 02142 USA

[4] Univ Maryland, Greenebaum Canc Ctr, Baltimore, MD 21201 USA

来源：

GENOME BIOLOGY | 2021年 / 22卷 / 01期

关键词：

RNA-Seq; Transcriptomics; Best practices; Differential gene expression; SINGLE-CELL; MESSENGER-RNA; GENE-EXPRESSION; HOST; PATHOGEN; TRANSCRIPTOME; GENOME; BACTERIAL; QUANTIFICATION; EFFICIENT;

D O I：

10.1186/s13059-021-02337-8

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

引用

页数：23

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