carma-package: Calculate CARMA scores
In arnevpladsen/CARMA: Calculate CARMA scores

Description Details Author(s) References Examples

The package provides functions for calculating CARMA scores within genomic regions from segmented DNA copy number profiles. The CARMA scores are numeric scores that reflect the presence of specific genomic motifs within the selected regions.

The main function in the carma package is the CARMA function. Input for the function is a list of length samples, containing data frames with segmented integer copy number data. Test data is supplied in the object test.data and shows the format of the input data. CARMA scores can be converted to summary tables using the summaryCARMA function. Regional CARMA scores can also be mapped to genes using the genesCARMA function. The package addtionally supplies plotting functions: per sample using the plotSample function, or across a dataset using the plotDataset function.

Authors: Arne Pladsen [aut, cre], Gro Nilsen [aut], Ole Christian Lingjærde [aut]

Maintainer: Arne Pladsen <arne.v.pladsen@gmail.com>

http://biorxiv.org/lookup/doi/10.1101/769356

# Format of input copy number profiles
head(test.data[[1]])

# Calculate CARMA scores per chromosome arm
carma.res <- CARMA(test.data, region.type="arm", hg="hg19")

# Calculate CARMA scores per whole chromosome
carma.res <- CARMA(test.data, region.type="chrom", hg="hg19")

# Calculate CARMA scores within 3*10^7 base pairs long regions
carma.res <- CARMA(test.data, region.type="bin", bin.width=3*10^7, hg="hg19")

# Plot CARMA scores per sample 
carma.res <- CARMA(test.data, region.type="arm", hg="hg19")
plotSample(carma.res, samples=c(1,2,3), plot.dir="~/Desktop/")

# Plot CARMA scores across the whole dataset
plotDataset(carma.res, plot.path="~/Desktop/carma_scores_entire_dataset.png")

# Plot CARMA scores across groups in the dataset
plotDataset(carma.res, group=rep(c("pos", "neg"), 50), 
	group.order=c("neg", "pos"), plot.titles=c("Negative", "Positive"), 
	plot.path="~/Desktop/carma_scores_groups.png", n.plot.cols=3)