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scTPA: A web tool for single-cell transcriptome analysis of pathway activation signatures
- Publication Year :
- 2020
- Publisher :
- Cold Spring Harbor Laboratory, 2020.
-
Abstract
- Motivation 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. Results 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. Availability and implementation http://sctpa.bio-data.cn/sctpa. Contact sujz@wmu.edu.cn or yufulong421@gmail.com or zgj@zjut.edu.cn Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects :
- Statistics and Probability
Cell type
Computer science
Interface (computing)
Cell
Computational biology
Biochemistry
Biological pathway
Transcriptome
Mice
03 medical and health sciences
0302 clinical medicine
Single-cell analysis
medicine
Animals
Cluster analysis
Molecular Biology
Gene
030304 developmental biology
0303 health sciences
Sequence Analysis, RNA
Gene Expression Profiling
Computer Science Applications
Gene expression profiling
Computational Mathematics
medicine.anatomical_structure
Computational Theory and Mathematics
Identification (biology)
Single-Cell Analysis
Software
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....648a6a8060a14000ad7d1c2985498588
- Full Text :
- https://doi.org/10.1101/2020.01.15.907592