Matrix factorization analyses of the immgenT scRNA-seq data

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Last updated: 2026-07-02

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Knit directory: immgenT-GP-analysis/analysis/

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This site documents the gene program (GP) factorization analysis of the ImmGen-T single-cell RNA-seq/CITE-seq data: ~200 GPs learned by empirical Bayes matrix factorization (EBMF), and how they relate to cell lineage, tissue, activation state, transcription factors, and surface protein expression.

Each page below covers one published figure: for every panel, the R code that produced it, the figure itself, and a short caption explaining what it shows.

Main figures

• Figure 1: Overview
• Figure 2: GPs and lineages
• Figure 3: GPs associated with T-cell activation
• Figure 4: GPs and tissue
• Figure 6: Linking GPs to proteins

Supplementary figures

• Figure S1: GP reproducibility across IGTs
• Figure S2: GP30 and GP58 loadings across T-cell subsets
• Figure S3: Characterizing activation GPs
• Figure S6: GP loadings recover protein-gated populations across GPs

Supplementary tables

• Table S1: per-GP summary

Reproducing these figures

Every page above is generated by a single R script in script-refactor/, which sources shared plotting/data-loading helpers from code-refactor/R/. To regenerate a figure yourself, run (from the repository root):

Rscript script-refactor/Figure1.R