Environment settings and input data
Typically, the user wants to record here the sources and versions of the
reference genome sequence along with the corresponding annotations. In
the provided sample data set all data inputs are stored in a data
subdirectory and all results will be written to a separate results directory,
while the systemPipeRNAseq.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.
To run this sample report, mini sample FASTQ and reference genome files can be downloaded from here. The chosen data set SRP010938 contains 18 paired-end (PE) read sets from Arabidposis thaliana (Howard et al., 2013). To minimize processing time during testing, each FASTQ file has been subsetted to 90,000-100,000 randomly sampled PE reads that map to the first 100,000 nucleotides of each chromosome of the A. thalina genome. The corresponding reference genome sequence (FASTA) and its GFF annotion files (provided in the same download) have been truncated accordingly. This way the entire test sample data set is less than 200MB in storage space. A PE read set has been chosen for this test data set for flexibility, because it can be used for testing both types of analysis routines requiring either SE (single end) reads or PE reads.
The following loads one of the available NGS workflow templates (here RNA-Seq) into the user’s current working directory. At the moment, the package includes workflow templates for RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Templates for additional NGS applications will be provided in the future.
library(systemPipeRdata)
genWorkenvir(workflow="rnaseq")
setwd("rnaseq")
Alternatively, this can be done from the command-line as follows:
$ Rscript -e "systemPipeRdata::genWorkenvir(workflow='rnaseq')"
$ cd rnaseq
Now download the latest systemPipeRNAseq.Rmd script for this course. From
within R this can be done as follows.
download.file("https://raw.githubusercontent.com/tgirke/GEN242/gh-pages/_vignettes/11_RNAseqWorkflow/systemPipeRNAseq.Rmd", "systemPipeRNAseq.Rmd")
Or from the command-line one can do this with wget.
$ wget -O systemPipeRNAseq.Rmd https://raw.githubusercontent.com/tgirke/GEN242/gh-pages/_vignettes/11_RNAseqWorkflow/systemPipeRNAseq.Rmd
If you work under Nvim-R-Tmux, the following command sequence will connect the user from the command-line to a computer node on the cluster.
$ srun --x11 --partition=short --mem=2gb --cpus-per-task 1 --ntasks 1 --time 2:00:00 --pty bash -l
Now open the R markdown script systemPipeRNAseq.Rmd in your R IDE (e.g.
nvim-r or RStudio) and run the workflow as outlined below.
Note, Tmux sessions should always run on one of the headnodes and never on the computer nodes themsleves. This is important since Tmux sessions are persistent meaning they don’t close automatically when a computer job finishes. Thus, they are not controlled by the queueing system.
To check the environment of R session, one can execute the following commands from R. The first line returns the node name of the R session.
system("hostname") # should return name of a compute node starting with i or c
getwd() # checks current working directory of R session
dir() # returns content of current working directory
Required packages and resources
The systemPipeR package needs to be loaded to perform the analysis steps shown in
this report (H Backman et al., 2016).
library(systemPipeR)
If applicable load custom functions not provided by
source("systemPipeRNAseq_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.txt", package="systemPipeR")
targets <- read.delim(targetspath, comment.char = "#")[,1:4]
targets
## FileName SampleName Factor SampleLong
## 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
## 4 ./data/SRR446030_1.fastq A1B A1 Avr.1h.B
## 5 ./data/SRR446031_1.fastq V1A V1 Vir.1h.A
## 6 ./data/SRR446032_1.fastq V1B V1 Vir.1h.B
## 7 ./data/SRR446033_1.fastq M6A M6 Mock.6h.A
## 8 ./data/SRR446034_1.fastq M6B M6 Mock.6h.B
## 9 ./data/SRR446035_1.fastq A6A A6 Avr.6h.A
## 10 ./data/SRR446036_1.fastq A6B A6 Avr.6h.B
## 11 ./data/SRR446037_1.fastq V6A V6 Vir.6h.A
## 12 ./data/SRR446038_1.fastq V6B V6 Vir.6h.B
## 13 ./data/SRR446039_1.fastq M12A M12 Mock.12h.A
## 14 ./data/SRR446040_1.fastq M12B M12 Mock.12h.B
## 15 ./data/SRR446041_1.fastq A12A A12 Avr.12h.A
## 16 ./data/SRR446042_1.fastq A12B A12 Avr.12h.B
## 17 ./data/SRR446043_1.fastq V12A V12 Vir.12h.A
## 18 ./data/SRR446044_1.fastq V12B V12 Vir.12h.B
Previous Page Next Page
