What question did this study set out to answer?

The aim is to provide reproducible analysis code and data supporting the manuscript on skin tumors originating from hair follicle stem cells.

May 9, 2026Open Access

Code and data for "Chemically-induced skin tumors arise from long-lived stem cells of the upper hair follicle"

Key Points

The aim is to provide reproducible analysis code and data supporting the manuscript on skin tumors originating from hair follicle stem cells.
Analysis includes single-cell RNA-seq workflows for HNSCC and cSCC.
Data processed through PCA, UMAP, and clustering techniques to identify tumor origins and characteristics.
Heatmap visualization displays mutation details across treatment groups.
Code and data structure allows for reproducibility in tumor analysis.
Findings include identification of prolonged stem cell involvement in skin tumor formation.
Heatmap visualizes mutation rates connected to RAS mutations across various treatments.

Abstract

This deposition contains the analysis code and supporting data used inthe manuscript "Chemically-induced skin tumors arise from long-livedstem cells of the upper hair follicle" by Kandyba et al. (Science, provisionally accepted; manuscript ID adv8291). The repository is organized by analysis/figure, with each subfoldercontaining code from a specific contributor along with a READMEdescribing inputs, outputs, and how to run the code: • HNSCCₐnalysis/ — single-cell RNA-seq analysis of head and neck squamous cell carcinoma (GEO: GSE181919, Choi et al. ). Standard Seurat workflow projecting the mouse Lgr6 carcinoma metagene onto HNSCC patients via mouse-to-human ortholog conversion (MGI), with metagene scoring by AddModuleScore. Used in Fig. S5. (R; author: Andrea Curtabbi) • humancSCCₐnalysis/ — Monocle3 analysis of human cutaneous squamous cell carcinoma (GEO: GSE144236, Ji et al. ) and the matched mouse cSCC dataset (GEO: GSE261766). PCA (100 components), UMAP (cosine; mindist=0. 1, nₙeighbors=15), Leiden clustering, patient-level alignment via aligncds, and projection of the Lgr6 carcinoma metagene and the Tsk signature from Ji et al. Used in Fig. S5. (R; author: Mark Taylor) • cellₒfₒriginₛcRNAseq/ — single-cell RNA-seq analysis of mouse Lgr6CreER-eGFP backskin (GEO: GSE261766) generated for this study, used to identify the cell of origin. CellRanger 3. 1 + Seurat 3. 2 pipeline with QC filtering (200–3000 genes/cell, <5% mitochondrial), yielding 3, 163 cells × 12, 768 genes; HVG selection, PCA, UMAP (top 15 PCs), and Louvain clustering. Used in Fig. 4 and Figs. S9–S11, S17–S18. (R; author: Yun Rose Li) • figure₆Bₕeatmap/ — self-contained reproducibility package for Fig. 6B: a log-scale heatmap of mutated cells per million across treatment groups, broken down by RAS mutation (Hras/Kras/Nras at codons 12, 13, and 61). Includes the visualization script, input data files (per-sample mutation calls and sequencing depths produced by deepUMIcaller and deepCSA), and reference output figures. (Python; author: Ferriol Calvet) Software requirements: R ≥ 4. 1 with Seurat, Monocle 3, and supportingpackages for the R analyses (cell-of-origin scripts originally runwith Seurat 3. 2 specifically) ; Python ≥ 3. 9 with pandas, matplotlib, seaborn, and numpy for the Fig. 6B heatmap. See the top-levelREADME. md for the complete dependency list and per-folder READMEs forcontribution-specific notes. The deposition is released under the Creative Commons Attribution 4. 0International (CC-BY-4. 0) license.

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