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SkillsMP has collected 12 skills from BrainStOrmics/BIA-CellHashtag. Open a skill to review its source and details.
Showing 12 of 12 collected skills.
DAG-MCTS for cell type annotation. Search space is a DAG (Merge + ReEmbed create multi-parent nodes). Uses P-UCT selection, Soft-Bellman backprop, confidence discounting, and transposition table. Per-iteration tree viz emitted as interactive HTML.
Correct batch effects in single-cell data using Harmony, BBKNN, or ComBat.
Query CellWiki knowledge base for marker genes, cell type ontologies, and tissue-specific cell type constraints.
Find differentially expressed genes (markers) for clusters using wilcoxon, t-test, or logistic regression. Includes consensus markers and resolution scanning.
Assess single-cell clustering quality using silhouette score, modularity, and phiclust. Returns recommendations to adjust resolution or accept current clustering.
Load single-cell RNA-seq data from h5ad, rds, or 10x mtx formats into AnnData objects.
Generate publication-quality UMAP/t-SNE embedding plots with Okabe-Ito color palette. Outputs PDF+PNG.
Generate violin plots and dot plots for gene expression visualization across cell clusters.
Generate marker gene heatmaps with hierarchical clustering dendrograms.
Compute QC metrics, filter cells, detect doublets for single-cell RNA-seq data.
Load spatial transcriptomics data from 10x Visium, Nanostring MERFISH, BGI Stereo-seq, and generic spatial formats.
Infer cell trajectories using PAGA graph-based trajectory inference.