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FreedomIntelligence/OpenClaw-Medical-SkillsView
Data & Repro
BI
bio-rna-quantification-count-matrix-qc
Maintainer FreedomIntelligence · Last updated April 1, 2026
QC count matrices: library size, zero inflation, gene detection rates.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-rna-quantification-count-matrix-qc
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- Quality control and exploratory analysis of count matrices before differential expression.
- dds <- DESeqDataSetFromTximport(txi, colData = coldata, design = ~ condition).
Source Doc
Excerpt From SKILL.md
From count matrix
counts <- read.csv('count_matrix.csv', row.names = 1) coldata <- data.frame(condition = factor(c('ctrl', 'ctrl', 'treat', 'treat')), row.names = colnames(counts)) dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata, design = ~ condition)
## Genes detected per sample
colSums(counts(dds) > 0)
## Counts summary
summary(colSums(counts(dds)))
Use cases
- Use bio-rna-quantification-count-matrix-qc for genomics and bioinformatics workflows.
- Apply bio-rna-quantification-count-matrix-qc to sequencing, variant, or omics analysis tasks.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- rna-quantification/featurecounts-counting - Generate counts
- rna-quantification/tximport-workflow - Import transcript counts
- differential-expression/de-visualization - Downstream visualization
- differential-expression/deseq2-basics - DE analysis
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