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  • Clustergrammer2 is an interactive WebGL heatmap Jupyter widget that is built to help researchers interactively explore single cell data (e.g. scRNA-seq). Clustergrammer2 enables unbiased hierarchical clustering, integration of prior knowledge categories, and the generation of novel signatures.
  • Platform: Python
  • Code: https://github.com/ismms-himc/clustergrammer2
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  • License: MIT
  • Categories: Classification, Clustering, Gene Sets, Interactive, Visualisation
  • Added: 2019-11-06, Updated: 2021-06-28

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  • scDECAF is a tool for mapping phenotype and celltype similarities in single cell RNAseq from a collection of genesets or makers such as those available from cellMarker, PanglaoDB and MSigDB
  • Platform: R
  • Code: https://github.com/DavisLaboratory/scDECAF
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  • License: GPL-3.0
  • Categories: Classification, Gene Sets
  • Added: 2021-06-04, Updated: 2021-06-04

  • SCPA is a method for pathway analysis in single cell RNA-seq data. It’s a novel approach to pathway analysis that defines pathway activity as a change in multivariate distribution of a given pathway across conditions, rather than enrichment or over representation of genes.

    • Publications
    • "Systematic single-cell pathway analysis to characterize early T cell activation"
      DOI: 10.1016/j.celrep.2022.111697, Published: 2022-11, Citations: 50
    • Preprints
    • "Systematic Single Cell Pathway Analysis (SCPA) reveals novel pathways engaged during early T cell activation"
      DOI: 10.1101/2022.02.07.478807, Citations: 0
  • Platform: R
  • Code: https://github.com/jackbibby1/SCPA
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  • License: GPL-3.0
  • Categories: Gene Sets, Visualisation
  • Added: 2022-02-11, Updated: 2023-01-04

  • SEPA provides convenient functions for users to assign genes into different gene expression patterns such as constant, monotone increasing and increasing then decreasing. SEPA then performs GO enrichment analysis to analysis the functional roles of genes with same or similar patterns.
  • Platform: R
  • Code: https://github.com/zji90/SEPA
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  • License: GPL-2.0-or-later
  • Categories: Expression Patterns, Gene Sets, Interactive
  • Added: 2016-09-08, Updated: 2016-09-08

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  • R package for differential expression (DE) analysis and gene set testing (GST) in single-cell RNA-seq (scRNA-seq) data

    • Publications
    • "TWO‐SIGMA: A novel two‐component single cell model‐based association method for single‐cell RNA‐seq data"
      DOI: 10.1002/gepi.22361, Published: 2020-09-29, Citations: 10
    • "TWO-SIGMA-G: a new competitive gene set testing framework for scRNA-seq data accounting for inter-gene and cell–cell correlation"
      DOI: 10.1093/bib/bbac084, Published: 2022-03-24, Citations: 5
    • Preprints
    • "TWO-SIGMA-G: A New Competitive Gene Set Testing Framework for scRNA-seq Data Accounting for Inter-Gene and Cell-Cell Correlation"
      DOI: 10.1101/2021.01.24.427979, Citations: 1
    • "TWO-SIGMA: a novel TWO-component SInGle cell Model-based Association method for single-cell RNA-seq data"
      DOI: 10.1101/709238, Citations: 1
  • Platform: R
  • Code: https://github.com/edvanburen/twosigma
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  • License: GPL-2.0
  • Categories: Differential Expression, Gene Sets, Simulation
  • Added: 2021-01-29, Updated: 2022-04-30

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