scTPA: A web tool for single-cell transcriptome analysis of pathway activation signatures

The most fundamental challenge in current single-cell RNA-seq data analysis is functional interpretation and annotation of cell clusters. The biological pathways in distinct cell types have different activation patterns, which facilitates understanding cell functions in single-cell transcriptomics. However, no effective web tool has been implemented for single-cell transcriptomic data analysis based on prior biological pathway knowledge. Here, we introduce scTPA (http://sctpa.bio-data.cn/sctpa), which is a web-based platform providing 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 pathway-oriented perspective. An intuitive interface allows users to conveniently visualize and download single-cell pathway signatures. Together, scTPA is a comprehensive tool to identify pathway activation signatures for dissecting single cell heterogeneity.

• Publication year

  2020

• Venue

  bioRxiv

• Publication date

  2020-01-15

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1101/2020.01.15.907592PMID 32437538
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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