Depth normalization of small RNA sequencing: using data and biology to select a suitable method.
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
10 06 2022
10 06 2022
Historique:
accepted:
08
02
2022
revised:
03
01
2022
received:
02
06
2021
pubmed:
22
2
2022
medline:
11
6
2022
entrez:
21
2
2022
Statut:
ppublish
Résumé
Deep sequencing has become one of the most popular tools for transcriptome profiling in biomedical studies. While an abundance of computational methods exists for 'normalizing' sequencing data to remove unwanted between-sample variations due to experimental handling, there is no consensus on which normalization is the most suitable for a given data set. To address this problem, we developed 'DANA'-an approach for assessing the performance of normalization methods for microRNA sequencing data based on biology-motivated and data-driven metrics. Our approach takes advantage of well-known biological features of microRNAs for their expression pattern and chromosomal clustering to simultaneously assess (i) how effectively normalization removes handling artifacts and (ii) how aptly normalization preserves biological signals. With DANA, we confirm that the performance of eight commonly used normalization methods vary widely across different data sets and provide guidance for selecting a suitable method for the data at hand. Hence, it should be adopted as a routine preprocessing step (preceding normalization) for microRNA sequencing data analysis. DANA is implemented in R and publicly available at https://github.com/LXQin/DANA.
Identifiants
pubmed: 35188574
pii: 6533612
doi: 10.1093/nar/gkac064
pmc: PMC9177987
doi:
Substances chimiques
MicroRNAs
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
e56Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Organisme : NHGRI NIH HHS
ID : R21 HG012124
Pays : United States
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.
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