Generate workflow environment
Load workflow environment with sample data into your current working directory. The sample data are described here.
library(systemPipeRdata) genWorkenvir(workflow = "varseq") setwd("varseq")
Alternatively, this can be done from the command-line as follows:
Rscript -e "systemPipeRdata::genWorkenvir(workflow='varseq')"
In the workflow environments generated by
genWorkenvir all data inputs are stored in
data/ directory and all analysis results will be written to a separate
results/ directory, while the
systemPipeVARseq.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
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.
Now open the R markdown script
systemPipeVARseq.Rmdin your R IDE (e.g. vim-r or RStudio) and
run the workflow as outlined below.
Here pair-end workflow example is provided. Please refer to the main vignette
systemPipeR.Rmd for running the workflow with single-end data.
Run R session on computer node
In a computer cluster enviornment. Typically, after opening the
Rmd file of
this workflow in Vim and attaching a connected R session via the
F2 ( vim-r
plugin installed) key, following command sequence can be used to run your R
session on a computer node.
q("no") # closes R session on head node
srun --x11 --partition=short --mem=2gb --cpus-per-task 4 --ntasks 1 --time 2:00:00 --pty bash -l module load R/3.6.0 R
Now check your R session running environment.
system("hostname") # should return the computer name or cluster name getwd() # checks current working directory of R session dir() # returns content of current working directory
systemPipeR package needs to be loaded to perform the analysis steps shown in
this report (H Backman et al., 2016).
If applicable users can load custom functions not provided by
this step if this is not the case.
If you are running on a single machine, use following code as an exmaple to check if some tools used in this workflow are in your environment PATH. No warning message should be shown if all tools are installed.