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
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epitranscriptomics/m6a-peak-calling - Generate peaks for visualization
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data-visualization/genome-tracks - IGV, UCSC integration
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chip-seq/chipseq-visualization - Similar techniques