ReddRadar
Agent 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 this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/bio-epitranscriptomics-modification-visualization
SKILL.md
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
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