Now open the R markdown script systemPipeChIPseq.Rmdin your R IDE (e.g. vim-r or RStudio) and
run the workflow as outlined below.
Load packages and sample data
The systemPipeR package needs to be loaded to perform the analysis steps shown in
this report (Girke , 2015).
library(systemPipeR)
Load workflow environment with sample data into your current working directory. The sample data are described here.
library(systemPipeRdata)
genWorkenvir(workflow="chipseq")
setwd("chipseq")
download.file("https://raw.githubusercontent.com/tgirke/GEN242/master/vignettes/12_ChIPseqWorkflow/systemPipeChIPseq.Rmd", "systemPipeChIPseq.Rmd")
In the workflow environments generated by genWorkenvir all data inputs are stored in
a data/ directory and all analysis results will be written to a separate
results/ directory, while the systemPipeChIPseq.Rmd script and the targets file are expected to be located in
the parent directory. The R session is expected to run from this parent
directory. Additional parameter files are stored under param/.
To work with real data, users want to organize their own data similarly
and substitute all test data for their own data. To rerun an established
workflow on new data, the initial targets file along with the corresponding
FASTQ files are usually the only inputs the user needs to provide.
If applicable users can load custom functions not provided by systemPipeR. Skip
this step if this is not the case.
source("systemPipeChIPseq_Fct.R")
Experiment definition provided by targets file
The targets file defines all FASTQ files and sample comparisons of the analysis workflow.
targetspath <- system.file("extdata", "targets_chip.txt", package="systemPipeR")
targets <- read.delim(targetspath, comment.char = "#")
targets[1:4,-c(5,6)]
## FileName SampleName Factor SampleLong SampleReference
## 1 ./data/SRR446027_1.fastq M1A M1 Mock.1h.A
## 2 ./data/SRR446028_1.fastq M1B M1 Mock.1h.B
## 3 ./data/SRR446029_1.fastq A1A A1 Avr.1h.A M1A
## 4 ./data/SRR446030_1.fastq A1B A1 Avr.1h.B M1B