runGAIA: Run GAIA algorithm.

In gaia: GAIA: An R package for genomic analysis of significant chromosomal aberrations.

Description

This function assess the significance of the chromosomal aberrations. Note that it uses the package qvalue.

Usage

runGAIA(cnv_obj, markers_obj, output_file_name, aberrations = -1, chromosomes = -1, num_iterations = 10, threshold = 0.25, hom_threshold = 0.12, approximation=FALSE)

Arguments

cnv_obj	an object returned by the function load_cnv describing the observed data.
markers_obj	an object returned by the function load_markers describing the observed markers.
output_file_name	the name of the file in which the significant aberrant regions are saved.
aberrations	[default=-1] the aberrations that will be analyzed. If it setted as -1 (default value) all aberrations will be analyzed.
chromosomes	[default=-1] the chromosomes that will be analyzed. If it setted as -1 (default value) all chromosomes will be analyzed.
num_iterations	[default=10] if the number of permutation steps (if approximation is equal to -1) - the number of column of the approximation matrix (if approximation is different to -1).
threshold	[default=0.25] markers having q-value lower than this threshold are labeled as significantly aberrant.
hom_threshold	[default=0.12] Threshold used for homogeneous peel-off. For values lower then 0 homogeneous peel-off is disabled.
approximation	[default=FALSE] if approximation is FALSE then GAIA explicitly performs the permutations, if it is TRUE then GAIA uses an approximated approach to compute the null distribution.

Value

This function return a matrix containing all significant aberrant regions.

Note

In order to execute this script you need of the R package qvalue available at the bioconductor repository.
To install the qvalue package, start R and enter:
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("qvalue")

Author(s)

Sandro Morganella et al.

Maintainer: S. Morganella <[e-mail]>

References

GAIA home page: http://www.dsba.unisannio.it/Members/ceccarelli/GAIA

Examples

# Load the matrix containing the informations about the markers
data(synthMarkers_Matrix)

# Use the function load_markers to obtain the marker descriptor data object
markers_obj <- load_markers(synthMarkers_Matrix)

# Load the matrix containing the informations about the aberrant regions
data(synthCNV_Matrix)

# Use the function load_cnv to obtain the aberrant region descriptor data object
cnv_obj <- load_cnv(synthCNV_Matrix, markers_obj, 10)

# run GAIA algorithm and save the results within the file "results.txt"
runGAIA(cnv_obj, markers_obj, "results.txt")

# run GAIA algorithm in its approximated version generating 5000 approximations
runGAIA(cnv_obj, markers_obj, "results.txt", num_iterations=5000, approximation=TRUE)

gaia documentation built on Nov. 8, 2020, 8:02 p.m.