Skill OpenCode
Read, write, create, merge, and convert single-cell data objects (AnnData/Scanpy and Seurat) for downstream analysis.
Skill OpenCode
Read, write, create, merge, and convert single-cell data objects (AnnData/Scanpy and Seurat) for downstream analysis.
Skill OpenCode
Sequence-based deep learning (chromBPNet, tangermeme, TF-MoDISco) for ATAC-seq: Tn5 bias correction, variant effect prediction, and de novo motif discovery.
Skill OpenCode
Choose and produce publication-quality 2D dimensionality-reduction plots (PCA, t-SNE, UMAP, PHATE) with deliberate hyperparameters and honest interpretation limits.
Skill OpenCode
Identify differentially methylated regions (DMRs) from WGBS or methylation-array data using tiling, smoothing, or kernel-based approaches, then refine, annotate, visualize, and export them.
Skill OpenCode
Detect and remove cell doublets from flow cytometry or CyTOF data using scatter gating, DNA/event-length methods, or regression residuals, with batch processing and visualization.
Skill OpenCode
Predict which gene a distal accessible (enhancer) region regulates by combining accessibility activity, 3D contact frequency, and sequence features into a per-(enhancer, gene) score; validate with CRISPRi-FlowFISH.
Skill OpenCode
Detect and remove cell doublets/aggregates from flow cytometry or CyTOF data using scatter gating, automated/QC methods, regression/ratio scoring, and CyTOF DNA/event-length detection, before clustering or quantitative analysis.
Skill OpenCode
Infer gene regulatory networks from single-cell data (pySCENIC for RNA-only, SCENIC+ for Multiome) and simulate TF perturbations with CellOracle.
Skill OpenCode
Estimate SNP heritability and partition it across functional categories, cell types, and loci using LDSC, LDAK SumHer, HDL, and HESS.
Skill OpenCode
Interactively annotate cell types in multiplexed imaging (IMC) data using napari visualization with marker overlays, then extract training data, propagate labels with KNN, and validate annotations.
Skill OpenCode
Reconstruct cell lineage trees from CRISPR/lentiviral/mitochondrial barcodes and analyze clonal dynamics and fate decisions in single-cell lineage-tracing experiments.
Skill OpenCode
Find differentially expressed marker genes per cluster, visualize them, score gene sets/cell cycle, and manually annotate cell types. Supports Scanpy (Python) and Seurat (R).
Skill OpenCode
Build publication-ready figures in Python with matplotlib's object-oriented Figure/Axes API, seaborn integration, Type-42 fonts, CVD-safe palettes, and rasterized point layers.
Skill OpenCode
Infer metabolite-mediated cell-cell communication from scRNA-seq data using MeboCost, by predicting metabolite secretion from enzyme expression and sensing via receptors.
Skill OpenCode
Compute per-sample/per-cell TF motif accessibility deviation z-scores with chromVAR (bulk, Signac, ArchR) and optionally refine TF activity with DecoupleR.
Skill OpenCode
Jointly analyze multimodal single-cell data (CITE-seq RNA+protein, 10X Multiome RNA+ATAC) using Weighted Nearest Neighbors (WNN) or Multi-Omics Factor Analysis (MOFA) integration.
Skill OpenCode
Complete 10X Multiome (joint scRNA + scATAC) analysis workflow using Seurat and Signac: load joint data, modality-specific QC and dimensionality reduction, WNN integration, clustering, markers, and gene-peak linkage.
Skill OpenCode
Build enhancer-driven gene regulatory networks (eRegulons) from paired scRNA+scATAC multiome data using SCENIC+, with a FigR alternative in R.
Skill OpenCode
Normalize raw RNA-seq count matrices: pre-filter genes, estimate between-sample size factors (RLE/TMM), compute TPM, variance-stabilize for visualization, correct GC/length bias, and normalize single-cell data.
Skill OpenCode
Annotate ChIP-seq / ATAC-seq peaks with gene features, ENCODE cCRE regulatory classes, and gene-set enrichment using ChIPseeker, HOMER, rGREAT, and ChIP-Enrich.
Skill OpenCode
Analyze a single-cell pooled CRISPR perturbation screen: assign sgRNAs to cells, filter escapers via Mixscape, fit per-gene differential expression (SCEPTRE/PyDESeq2), and rank perturbations by molecular effect.
Skill OpenCode
Analyze Perturb-seq CRISPR screens by linking guide RNA assignments to single-cell transcriptional phenotypes using pertpy and Seurat Mixscape.
Skill OpenCode
Assign cell types to segmented IMC single cells from protein marker expression via Leiden clustering, manual gating, or SOM/supervised classification.
Skill OpenCode
Preprocess scRNA-seq data: QC metrics, filtering, normalization, highly variable gene selection, and scaling for downstream analysis. Covers Scanpy (Python) and Seurat (R).
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: