Best practices on the differential expression analysis of multi-species RNA-seq.
Animals
Eukaryota
/ genetics
Gene Expression Profiling
/ methods
Gene Expression Regulation
High-Throughput Nucleotide Sequencing
Humans
Organ Specificity
Prokaryotic Cells
/ metabolism
RNA
/ genetics
RNA-Seq
/ methods
ROC Curve
Sequence Alignment
Sequence Analysis, RNA
/ methods
Single-Cell Analysis
/ methods
Transcriptome
Workflow
Best practices
Differential gene expression
RNA-Seq
Transcriptomics
Journal
Genome biology
ISSN: 1474-760X
Titre abrégé: Genome Biol
Pays: England
ID NLM: 100960660
Informations de publication
Date de publication:
29 04 2021
29 04 2021
Historique:
received:
21
10
2020
accepted:
01
04
2021
entrez:
30
4
2021
pubmed:
1
5
2021
medline:
15
1
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33926528
doi: 10.1186/s13059-021-02337-8
pii: 10.1186/s13059-021-02337-8
pmc: PMC8082843
doi:
Substances chimiques
RNA
63231-63-0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
121Subventions
Organisme : NIAID NIH HHS
ID : U19 AI110818
Pays : United States
Organisme : NIAID NIH HHS
ID : U19 AI110820
Pays : United States
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