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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
Published on: January 10, 2019
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Annotation of cell types (ACT): a convenient web server for cell type annotation
Fei Quan1, Xin Liang1, Mingjiang Cheng1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Genome Medicine
|November 4, 2023
Summary
Manual cell type annotation is slow and requires expertise. We developed ACT, a web server using a curated marker map and a novel gene set enrichment method, to rapidly and accurately identify cell types in single-cell sequencing data.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Single-cell sequencing advances biological research but generates massive datasets.
- Accurate cell type annotation is crucial for interpreting these datasets.
- Current manual annotation methods are time-consuming and require specialized knowledge.
Purpose of the Study:
- To develop an automated and efficient method for cell type annotation in single-cell data.
- To create a user-friendly tool that overcomes the limitations of manual annotation.
- To accelerate the analysis and interpretation of large-scale single-cell datasets.
Main Methods:
- Constructed a hierarchical cell marker map from extensive literature curation (approx. 7000 publications).
- Developed WISE (weighted and integrated gene set enrichment), a novel method integrating marker prevalence and gene expression order.
- Integrated the marker map and WISE into a web server named ACT (Automated Cell Type annotation).
Main Results:
- The ACT web server provides interactive hierarchy maps and statistical information from a simple gene list input.
- ACT demonstrated superior performance compared to state-of-the-art methods in benchmarking analyses.
- Case studies showed ACT rapidly and accurately annotated cell clusters, identifying multi-level cell types.
Conclusions:
- ACT offers a powerful, knowledge-based resource and an intuitive graphical interface for cell type annotation.
- This tool significantly accelerates cell type identification in single-cell research.
- ACT is expected to become a widely adopted tool in the field of single-cell genomics.
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