Awesome-omni-skill bio-epitranscriptomics-modification-visualization
Create metagene plots and browser tracks for RNA modification data. Use when visualizing m6A distribution patterns around genomic features like stop codons.
install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/development/bio-epitranscriptomics-modification-visualization" ~/.claude/skills/diegosouzapw-awesome-omni-skill-bio-epitranscriptomics-modification-visualizatio && rm -rf "$T"
manifest:
skills/development/bio-epitranscriptomics-modification-visualization/SKILL.mdsource content
Modification Visualization
Metagene Plots with Guitar
library(Guitar) library(TxDb.Hsapiens.UCSC.hg38.knownGene) # Load m6A peaks peaks <- import('m6a_peaks.bed') # Create metagene plot # Shows distribution relative to transcript features GuitarPlot( peaks, txdb = TxDb.Hsapiens.UCSC.hg38.knownGene, saveToPDFprefix = 'm6a_metagene' )
Custom Metagene with deepTools
# Create bigWig from IP/Input ratio bamCompare -b1 IP.bam -b2 Input.bam \ --scaleFactors 1:1 \ --ratio log2 \ -o IP_over_Input.bw # Metagene around stop codons computeMatrix scale-regions \ -S IP_over_Input.bw \ -R genes.bed \ --regionBodyLength 2000 \ -a 500 -b 500 \ -o matrix.gz plotProfile -m matrix.gz -o metagene.pdf
Browser Tracks
# Create normalized bigWig for genome browser bamCoverage -b IP.bam \ --normalizeUsing CPM \ -o IP_normalized.bw # Peak BED to bigBed bedToBigBed m6a_peaks.bed chrom.sizes m6a_peaks.bb
Heatmaps
library(ComplexHeatmap) # m6A signal around peaks Heatmap( signal_matrix, name = 'm6A signal', cluster_rows = TRUE, show_row_names = FALSE )
Related Skills
- epitranscriptomics/m6a-peak-calling - Generate peaks for visualization
- data-visualization/genome-tracks - IGV, UCSC integration
- chip-seq/chipseq-visualization - Similar techniques