ArticleCommunications biology2022
Multi-level cellular and functional annotation of single-cell transcriptomes using scPipeline.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Integrated Genetic Screening Identifies FEN1 as a Selective Vulnerability and Temozolomide Resistance Mediator in Glioblastoma Stem Cells.Cancer research communications · 2026Article
- New biological insights into osteosarcoma-lessons from single cell sequencing studies.Cancer metastasis reviews · 2026Review
- Network-informed deconvolution of bulk immune gene co-expression reveals single-cell programs and spatial organization.Frontiers in immunology · 2026Article
- Mapping Cell Identity from scRNA-seq: A primer on computational methods.Computational and structural biotechnology journal · 2025Review
- Functional profiling of murine glioma models highlights targetable immune evasion phenotypes.Acta neuropathologica · 2024Article
- A self-training interpretable cell type annotation framework using specific marker gene.Bioinformatics (Oxford, England) · 2024Article
- Article
- Single-nucleus atlas of the Artemia female reproductive system suggests germline repression of the Z chromosome.PLoS genetics · 2024Article
- CD200Nature immunology · 2024Article
- CAP-RNAseq: an integrated pipeline for functional annotation and prioritization of co-expression clusters.Briefings in bioinformatics · 2024Article
- The proteomic landscape of glioblastoma recurrence reveals novel and targetable immunoregulatory drivers.Acta neuropathologica · 2022Article
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Authors and funding
6 authors.
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Abstract
Single-cell RNA-sequencing (scRNA-seq) offers functional insight into complex biology, allowing for the interrogation of cellular populations and gene expression programs at single-cell resolution. Here, we introduce scPipeline, a single-cell data analysis toolbox that builds on existing methods and offers modular workflows for multi-level cellular annotation and user-friendly analysis reports. Advances to scRNA-seq annotation include: (i) co-dependency index (CDI)-based differential expression, (ii) cluster resolution optimization using a marker-specificity criterion, (iii) marker-based cell-type annotation with Miko scoring, and (iv) gene program discovery using scale-free shared nearest neighbor network (SSN) analysis. Both unsupervised and supervised procedures were validated using a diverse collection of scRNA-seq datasets and illustrative examples of cellular transcriptomic annotation of developmental and immunological scRNA-seq atlases are provided herein. Overall, scPipeline offers a flexible computational framework for in-depth scRNA-seq analysis.
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