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
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

4217-4219

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Yan Zhang (Y)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

Yaru Zhang (Y)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

Jun Hu (J)

College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China.

Ji Zhang (J)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

Fangjie Guo (F)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

Meng Zhou (M)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

Guijun Zhang (G)

College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China.

Fulong Yu (F)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

Jianzhong Su (J)

School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.

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