SCI Skills

CN Directory
数据与复现单细胞与空间组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
BI

bio-single-cell-markers-annotation

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Find marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for differential expression between clusters, identifying cluster-specific markers, scoring gene sets, and assigning cell type labels. Use when finding marker genes and annotating clusters.

OpenClawNanoClaw分析处理复现实验bio-single-cell-markers-annotation🧬 bioinformatics (gptomics bio-* suite)bioinformatics — single-cell & spatial omicsfind

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-single-cell-markers-annotation

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • Find differentially expressed genes between clusters 、 annotate cell types。
  • sc.tl.rank_genes_groups(adata，groupby='leiden'，method='wilcoxon')。

原始文档

SKILL.md 摘录

Scanpy (Python)

Goal: Identify cluster-specific marker genes, score gene sets, and annotate cell types using Scanpy.

Approach: Perform differential expression testing between clusters with Wilcoxon rank-sum, visualize markers with dot plots and heatmaps, and assign cell type labels manually.

"Find marker genes for each cluster" → Test each cluster against all others for differentially expressed genes and rank by statistical significance and fold change.

View top markers

sc.pl.rank_genes_groups(adata, n_genes=10, sharey=False)

Get results as DataFrame

markers = sc.get.rank_genes_groups_df(adata, group=None) print(markers.head(20))

适用场景

  • 可用于differential expression between clusters，identifying cluster-specific markers，scoring gene sets，、 assigning cell type labels。
  • 适合在finding marker genes 、 annotating clusters时使用。

不适用场景

  • Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。

上游相关技能

  • clustering - Must cluster before finding markers
  • preprocessing - Data must be normalized
  • data-io - Export annotated data

相关技能

相关技能

返回目录
AN
数据与复现单细胞与空间组学

AnnData

AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observ…

Claude CodeOpenClaw分析处理
K-Dense-AI/claude-scientific-skills查看
AR
数据与复现单细胞与空间组学

Arboreto

Arboreto is a computational library for inferring gene regulatory networks (GRNs) from gene expression data using parall…

Claude CodeOpenClaw分析处理
K-Dense-AI/claude-scientific-skills查看
BI
数据与复现单细胞与空间组学

bio-imaging-mass-cytometry-cell-segmentation

Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for n…

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看
BI
数据与复现单细胞与空间组学

bio-read-qc-umi-processing

Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep…

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看