Bio epitranscriptomics modification visualization

Skill FridrichMethod/awesome-skills/skills/bio-epitranscriptomics-modification-visualization

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Install

npx -y skills add FridrichMethod/awesome-skills --skill bio-epitranscriptomics-modification-visualization

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What its author says it does

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Create metagene plots and browser tracks for RNA modification data. Use when visualizing m6A distribution patterns around genomic features like stop codons.

SKILL.md

2.2 KB, as published. Nobody here has run it

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