MLGenSig

Machine Learning for Genetic Signatures

MLExpResso

Package for analyzing genes expression and CpG probes methylation.

Online Manual

News

Imports installation

Our package uses a few packages from Bioconductor. To install them, start R and enter

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("DESeq")

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("DESeq2")

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("limma")

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("edgeR")

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("methyAnalysis")

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("TxDb.Hsapiens.UCSC.hg18.knownGene")

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("org.Hs.eg.db")

Installation

To install this package, start R and enter:

devtools::install_github("geneticsMiNIng/MLGenSig/MLExpResso")

In order to run examples you shall install MLExpRessoData.

devtools::install_github("geneticsMiNIng/MLGenSigdata/MLExpRessodata")

User Guide

• Quick start
• Cheatsheet
• Automatically created report and Instruction

Scripts and datasets

• Full BRCA mRNAseq data
• Full BRCA mRNAseq data with subtypes
• BRCA clinical data with parameters
• BRCA clinical data w/o parameters

Example dashboards

Acknowledgments

Work on this package was financially supported by the ‘NCN Opus grant 2016/21/B/ST6/02176’.