SinomeM/cnv_geaRs: A little gear kit to manage CNV calling results

This package contains a set of functions that can be useful when interpreting the results of a CNV calling algorithm or pipeline. It was designed to merge and analyze the results of two different pipelines using Illumina SNP array data from an ASD related study, but can be used in various situation. In particular the locus() function is useful per se as an easy way to add the chromosomal locus information to large datasets of CNV-like entries (anything consisting of "chr", "start", "end", potentially also a gene) being optimized for parallel processing. Originally it was used as a preprocessing step for the inter_comp() function. lrr_plot() function instead is specifically designed for Illumina array data and takes as input a file in the format of "FinalReport" and plots LRR values. Also inter_comp() is specifically desgigned for array data and for comparison uses the number of common markers (SNPs) instead of raw chromosomal coordinate. The following packages are required for cnvgeaRs functions to work: "dplyr", "magrittr", "ggplot2", "data.table", "foreach", "doParallel", "RcppRoll", "stats".

Getting started

Package details

AuthorSimone Montalbano
MaintainerSimone Montalbano <simone.montalbano@protonmail.com>
LicenseGPL-3
Version0.1.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("SinomeM/cnv_geaRs")
SinomeM/cnv_geaRs documentation built on Dec. 4, 2020, 3:06 a.m.