bio-atac-seq-motif-deviation
Analyze transcription factor motif accessibility variability using chromVAR. Use when identifying which TF motifs show variable accessibility across samples or conditions in ATAC-seq data.
npx skills add majiayu000/claude-skill-registry --skill motif-deviation-gptomics-bioskills --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Motif Deviation Analysis Measure per-sample variability in transcription factor motif accessibility using chromVAR. This identifies TFs whose binding sites show differential accessibility across conditions. ## Required Packages ```r library(chromVAR) library(motifmatchr) library(BSgenome.Hsapiens.UCSC.hg38) # or appropriate genome library(JASPAR2020) library(TFBSTools) library(SummarizedExperiment) ``` ## Basic Workflow ### 1. Load Peak Counts ```r library(chromVAR) library(SummarizedExperiment) # From count matrix and peak ranges peaks <- read.table('peaks.bed', col.names = c('chr', 'start', 'end')) peak_ranges <- GRanges(seqnames = peaks$chr, ranges = IRanges(peaks$start, peaks$end)) counts <- read.table('counts.txt', header = TRUE, row.names = 1) counts_matrix <- as.matrix(counts) fragment_counts <- SummarizedExperiment( assays = list(counts = counts_matrix), rowRanges = peak_ranges ) ``` ### 2. Add GC Bias Correction ```r library(BSgenome.Hsapiens.UCSC.hg38) fragment_counts <- addGCBias(fragment_counts, genome = BSgenome.Hsapiens.UCSC.hg38) ``` ### 3. Filter Low-Quality Peaks ```r # min_depth=1500: Minimum total reads per sample. Adjust based on library size. # min_in_peaks=0
- Required Packages
- Basic Workflow
- 1. Load Peak Counts
- 2. Add GC Bias Correction
- 3. Filter Low-Quality Peaks
- Get Motif Annotations
- From JASPAR
- From CIS-BP or Custom PWMs
- Compute Deviations
- Interpreting Results
- Deviation Scores
- Variability Interpretation
- Visualization
- Deviation Heatmap
What does the bio-atac-seq-motif-deviation skill do?
Analyze transcription factor motif accessibility variability using chromVAR. Use when identifying which TF motifs show variable accessibility across samples or conditions in ATAC-seq data.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill motif-deviation-gptomics-bioskills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.