GOTHiChicup: Genome Organisation Through HiC from HiCUP output
In borimifsud/GOTHiC: Binomial test for Hi-C data analysis

Description Usage Arguments Value Author(s) See Also Examples

View source: R/GOTHiC.R

GOTHiChicup performs a cumulative binomial test to detect interactions between distal genomic loci that have significantly more reads than expected by chance in Hi-C experiments. It takes mapped and filtered paired NGS reads from HiCUP as input and gives back the list of significant interactions for a given bin size in the genome.

1	GOTHiChicup(fileName, sampleName, res, restrictionFile, cistrans='all', parallel=FALSE, cores=NULL)

`fileName`	A character string with the name of the file containing the mapped, filtered reads from HiCUP, after the default HiCUP output is converted to a table containing only the first 4 columns (read ID, flag, chromosome and start positions). Can be gzipped. (Tab separated text format)
`sampleName`	A character string that will be used to name the quality control plot. It will be saved in the current directory.
`res`	An integer that gives the required bin size or resolution of the contact map e.g. 1000000, for fragment level use 1.
`restrictionFile`	A character string with the name of the digest file from HiCUP. It is used to map reads to restriction fragments. (.txt file name)
`cistrans`	A character string with three possibilities. "all" runs the binomial test on all interactions, "cis" runs the binomial test only on intrachromosomal/cis interactions, "trans" runs the binomial test only on interchromosomal/trans interactions.
`parallel`	Logical argument. If TRUE the mapping and the binomial test will be performed faster using multiple cores. The default is FALSE.
`cores`	An integer specifying the number of cores used in the parallel processing if parellel=TRUE. The default is NULL.

A data.frame containing elements

`chr1 / chr2`	chromosome(s) containing interacting regions 1 and 2
`locus1 / locus2`	start positions of the interacting regions 1 and 2 in the corresponding chromosome(s)
`relCoverage1 / relCoverage2`	relative coverage corresponding to regions 1 and 2
`probability`	expected frequency
`expected`	expected number of reads
`readCount`	observed reads number
`pvalue`	binomial p-value
`qvalue`	binomial p-value corrected for multi-testing with Benjamini-Hochberg
`logObservedOverExpected`	observed/expected read numbers log ratio

Borbala Mifsud and Robert Sugar

binom.test

library(GOTHiC)
dirPath <- system.file("extdata", package="HiCDataLymphoblast")
fileName <- list.files(dirPath, full.names=TRUE)[4]
restrictionFile <- list.files(dirPath, full.names=TRUE)[3]
binom=GOTHiChicup(fileName, sampleName='lymphoid_chr20', res=1000000, 
restrictionFile, cistrans='all', parallel=FALSE, cores=NULL)