bin_fragment_size: Gets histogram of fragment lengths from a bam file
In ctDNAtools: Analyze Circulating Tumor DNA Sequencing Data

Description Usage Arguments Details Value See Also Examples

The function first extracts fragment length from a bam file then computes the histogram over defined bins. If normalized is TRUE, the counts per bin will be normalized to the total read counts. Optionally, it can computes the histogram of fragment lengths only for mutated reads (confirmed ctDNA molecules).

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bin_fragment_size(bam, mutations = NULL, targets = NULL, tag = "",
  bin_size = 2, custom_bins = NULL, normalized = FALSE,
  min_size = 1, max_size = 400, ...)

`bam`	path to bam file.
`mutations`	An optional data frame with mutations. Must have the columns CHROM, POS, REF, ALT.
`targets`	a data frame with the target regions to restrict the reads in the bam. Must have three columns: chr, start and end
`tag`	the RG tag if the bam has more than one sample.
`bin_size`	the width of the bin (breaks) of the histogram.
`custom_bins`	A numeric vector for custom breaks to bin the histogram of fragment length. Over-rides bin_size.
`normalized`	A logical, whether to normalize the counts to the total number of reads.
`min_size`	Integer with the lowest fragment length.
`max_size`	Integer with the highest fragment length.
`...`	Other parameters passed to get_fragment_size.

Fragment length will extracted from the bam file according to the parameters passed to get_fragment_size, and histogram counts (optionally normalized to total counts) are computed. Both equal histogram bins via bin_size and manually customized bins via custom_bins are supported.

By using an input mutations, the function will bin separately the reads that support variant alleles, reference alleles and other reads.

A data frame with one column for the used breaks and one having the histogram (normalized) counts. If mutations is supplied, the output will have one breaks column and three columns corresponding to variant allele reads, reference allele reads, and other reads. Each row has the count of fragment lengths within the bin and optionally normalized by the total number of reads.

get_fragment_size analyze_fragmentation summarize_fragment_size

data("targets", package = "ctDNAtools")
data("mutations", package = "ctDNAtools")
bamT1 <- system.file("extdata", "T1.bam", package = "ctDNAtools")

## basic usage
bin_fragment_size(bam = bamT1)

## with normalization
bin_fragment_size(bam = bamT1, normalized = TRUE)


## binning reads categorized based on mutations ref and alt
bin_fragment_size(bam = bamT1, mutations = mutations)

## Restrict to reads into targets
bin_fragment_size(bam = bamT1, targets = targets)