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SkillsMP는 BrainStOrmics/BIA-CellHashtag에서 12개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 12개 중 12개를 표시합니다.
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.
원문 언어: 영어
Correct batch effects in single-cell data using Harmony, BBKNN, or ComBat.
원문 언어: 영어
Query CellWiki knowledge base for marker genes, cell type ontologies, and tissue-specific cell type constraints.
원문 언어: 영어
Find differentially expressed genes (markers) for clusters using wilcoxon, t-test, or logistic regression. Includes consensus markers and resolution scanning.
원문 언어: 영어
Assess single-cell clustering quality using silhouette score, modularity, and phiclust. Returns recommendations to adjust resolution or accept current clustering.
원문 언어: 영어
Load single-cell RNA-seq data from h5ad, rds, or 10x mtx formats into AnnData objects.
원문 언어: 영어
Generate publication-quality UMAP/t-SNE embedding plots with Okabe-Ito color palette. Outputs PDF+PNG.
원문 언어: 영어
Generate violin plots and dot plots for gene expression visualization across cell clusters.
원문 언어: 영어
Generate marker gene heatmaps with hierarchical clustering dendrograms.
원문 언어: 영어
Compute QC metrics, filter cells, detect doublets for single-cell RNA-seq data.
원문 언어: 영어
Load spatial transcriptomics data from 10x Visium, Nanostring MERFISH, BGI Stereo-seq, and generic spatial formats.
원문 언어: 영어
Infer cell trajectories using PAGA graph-based trajectory inference.
원문 언어: 영어