## 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


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