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bio-workflows-scrnaseq-pipeline

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

Single-cell RNA-seq end-to-end: Cell Ranger → Scanpy → clustering.

OpenClawNanoClaw分析处理复现实验bio-workflows-scrnaseq-pipeline🧠 bioos extended suitebioos extended bioinformatics suitesingle

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-workflows-scrnaseq-pipeline

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

  • Complete workflow ，面向 10X Genomics Cell Ranger output to annotated cell types。
  • data_dir <- 'cellranger_output/filtered_feature_bc_matrix' counts <- Read10X(data.dir = data_dir)。

原始文档

SKILL.md 摘录

Step 1: Load 10X Data

library(Seurat)
library(ggplot2)
library(dplyr)

## Create Seurat object

seurat_obj <- CreateSeuratObject(counts = counts, project = 'my_project',
                                  min.cells = 3, min.features = 200)

Calculate QC metrics

seurat_obj[['percent.mt']] <- PercentageFeatureSet(seurat_obj, pattern = '^MT-') seurat_obj[['percent.ribo']] <- PercentageFeatureSet(seurat_obj, pattern = '^RP[SL]')

适用场景

  • Use bio-workflows-scrnaseq-pipeline ，用于 single-cell 或 spatial omics analysis。
  • Apply bio-workflows-scrnaseq-pipeline to 聚类，integration，或 trajectory workflows。

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

  • single-cell/data-io - Loading different formats
  • single-cell/preprocessing - QC details
  • single-cell/doublet-detection - Doublet methods comparison
  • single-cell/clustering - Clustering parameters
  • single-cell/markers-annotation - Annotation strategies
  • single-cell/multimodal-integration - CITE-seq, multiome

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