scTPA: a web tool for single-cell transcriptome analysis of pathway activation signatures.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
15 08 2020
15 08 2020
Historique:
received:
09
03
2020
revised:
13
05
2020
accepted:
15
05
2020
pubmed:
22
5
2020
medline:
2
2
2021
entrez:
22
5
2020
Statut:
ppublish
Résumé
At present, a fundamental challenge in single-cell RNA-sequencing data analysis is functional interpretation and annotation of cell clusters. Biological pathways in distinct cell types have different activation patterns, which facilitates the understanding of cell functions using single-cell transcriptomics. However, no effective web tool has been implemented for single-cell transcriptome data analysis based on prior biological pathway knowledge. Here, we present scTPA, a web-based platform for pathway-based analysis of single-cell RNA-seq data in human and mouse. scTPA incorporates four widely-used gene set enrichment methods to estimate the pathway activation scores of single cells based on a collection of available biological pathways with different functional and taxonomic classifications. The clustering analysis and cell-type-specific activation pathway identification were provided for the functional interpretation of cell types from a pathway-oriented perspective. An intuitive interface allows users to conveniently visualize and download single-cell pathway signatures. Overall, scTPA is a comprehensive tool for the identification of pathway activation signatures for the analysis of single cell heterogeneity. http://sctpa.bio-data.cn/sctpa. sujz@wmu.edu.cn or yufulong421@gmail.com or zgj@zjut.edu.cn. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 32437538
pii: 5841657
doi: 10.1093/bioinformatics/btaa532
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4217-4219Informations de copyright
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.