MOCCASIN: a method for correcting for known and unknown confounders in RNA splicing analysis.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
07 06 2021
07 06 2021
Historique:
received:
23
05
2020
accepted:
07
05
2021
entrez:
8
6
2021
pubmed:
9
6
2021
medline:
29
6
2021
Statut:
epublish
Résumé
The effects of confounding factors on gene expression analysis have been extensively studied following the introduction of high-throughput microarrays and subsequently RNA sequencing. In contrast, there is a lack of equivalent analysis and tools for RNA splicing. Here we first assess the effect of confounders on both expression and splicing quantifications in two large public RNA-Seq datasets (TARGET, ENCODE). We show quantification of splicing variations are affected at least as much as those of gene expression, revealing unwanted sources of variations in both datasets. Next, we develop MOCCASIN, a method to correct the effect of both known and unknown confounders on RNA splicing quantification and demonstrate MOCCASIN's effectiveness on both synthetic and real data. Code, synthetic and corrected datasets are all made available as resources.
Identifiants
pubmed: 34099673
doi: 10.1038/s41467-021-23608-9
pii: 10.1038/s41467-021-23608-9
pmc: PMC8184769
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
3353Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM128096
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM118048
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM008216
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA232563
Pays : United States
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