/scripts

Primary LanguageR

Scripts

RScripts and codes for analysis

Files

R scripts

  • Microarray_pipeline.R : Microarray analysis pipeline
  • RNAseqAnalysisPipeline.R : RNA-Seq analysis pipeline
  • scRNA_seurat_pipeline.R : Single cell RNA-Seq analysis pipeline using Seurat
  • aggr_seurat_cca.R : Single cell RNA-Seq analysis for aggregate data pipeline using Seurat
  • Seurat_v3.R : Single cell RNA-Seq analysis pipeline using Seurat version3 and scExtras package

Run STAR

  • run_STAR_singlepass.pl : Run STAR aligner on fastq files
  • parseSTARLog.pl : Read STAR Log.out files to create a summary of results
  • createsummary.R : Create STAR and Picard summary files into RData file to upload into STARSummary website

Requirements

Install following R packages.

MICROARRAY

install.packages(c("dplyr","plyr","tidyr","devtools","NMF","RColorBrewer","ggplot2","readr"))

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite(c("OligoTools","sva","limma","SPIA","oligo","topGO"))

#Install this package having additional functions
install_github('mpmorley/ExpressExtras')

RNA_Seq

install.packages(c("dplyr","plyr","tidyr","devtools","NMF","RColorBrewer","ggplot2","readr"))

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite(c("limma","edgeR","org.Mm.eg.db","EnsDb.Mmusculus.v75","SPIA"))

#Install this package having additional functions
install_github('mpmorley/ExpressExtras')
install_github('mpmorley/scExtras')

Single Cell RNA-Seq using Seurat

install.packages(c("dplyr","readr","Matrix","cowplot"))

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

STAR

Install and run STAR aligner. Instructions and documentation can be found here.

NOTE:

  • The RNA-Seq and Microarray scripts are written for data aligned using STAR. You have to edit the code for it to take an input of count data
  • The R scripts for analysing Microarray and RNA-Seq data requires a file listing the sample names and other meta-information. Please refer to the example file in data folder titled 'phenodata.csv'.
  • The sample names in phenodata.csv should match the sample names in the count matrix
  • The 'maineffect' column in phenodata.csv is required. This column specifies the effect that is being tested for
  • If you want to use a file for specifying contrasts instead of adding it to the script, refer to the file in the data folder titled 'contrastlist.csv'