In bigbio/PepBed: The PepBedR is an R-package to analyze peptide based Bed and bigBed files.

knitr::opts_chunk$set(echo = TRUE)

Parsing bigbed files

library(PepBedR)

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Parsing Bed file

# path to bed file(s)
bed_path <- '/Users/yperez/IdeaProjects/github-repo/BDP/benchmark/ensembl/GRCh38/PepGenome-Peptide-Atlas.bed'

# import bed file as  dataframe
bed_df <- readBedFile(inputFile = bed_path)
bed_df <- setBed12Columns(bed_df)

# convert dataframe to GRanges
# all non-modified peptides
granges_peptide <- buildGRangesFromData(data = bed_df, 
                                        chrColName = "chrom", 
                                        startColName = "chromStart", 
                                        endColName = "chromEnd") 

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Computing some basic stats from the data

# getting number of features(peptides) by chromosome
counts <- countsByChromosome(gr = granges_peptide, colName = 'Peptides')
print(counts)

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Getting stats for unique peptides

# removing duplicated entries from original granges_peptide
unique_pep <- getUniqueFeatures(granges_peptide, colFeatures = 'name')

# getting unique number of features(peptides) by chromosome
counts_unique <- countsByChromosome(gr = unique_pep, colName = 'Peptides')

print(counts_unique)

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Computing % coverage

## compute coverage of query (peptide evidences) on subject (transcripts) by crhomosome
data("protein_coding_transcript_hg38") # load protein coding transcript as GRanges object

coverage <- computeCoverageByChromosome(query = granges_peptide, 
                                        subject = transcripts_hg38, colName = 'Coverage')

print(coverage)

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Visualizing the data

• The distribution of peptides by chromosome. (red_track: peptides)

library(circlize)
circos.initializeWithIdeogram(species = 'hg19')
bed <- bed_df
circos.genomicDensity(bed, col = c("#FF000080"), track.height = 0.1, baseline = 0)
circos.clear()

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• barplot with coverage (all peptides) by chromosome

dat <- coverage

plot3 <- ggplot(dat, aes(x = factor(Chromosome, levels = unique(dat$Chromosome)), y = Coverage)) + 
         geom_col(fill='darkgreen', alpha=0.4) +
         labs(x = 'Chromosome', y = '% coverage', fill = '') +
         theme_bw() +
         theme(axis.text = element_text(size=12),
               axis.title = element_text(size=14),
               panel.grid.major = element_blank(),
               panel.grid.minor = element_blank(),
               axis.line = element_line(colour = "black"))
plot3

library(Sushi)
plotManhattan(bedfile=bed_path,cex=0.75)

bigbio/PepBed documentation built on May 28, 2019, 7:11 p.m.