```{css, echo=FALSE} pre code { white-space: pre !important; overflow-x: scroll !important; word-break: keep-all !important; word-wrap: initial !important; }

```r
BiocStyle::markdown()
options(width=60, max.print=1000)
knitr::opts_chunk$set(
    eval=as.logical(Sys.getenv("KNITR_EVAL", "TRUE")),
    cache=as.logical(Sys.getenv("KNITR_CACHE", "TRUE")), 
    tidy.opts=list(width.cutoff=60), tidy=TRUE)
suppressPackageStartupMessages({
    library(systemPipeR)
})

Workflow environment

systemPipeR workflows can be designed and built from start to finish with a single command, importing from an R Markdown file or stepwise in interactive mode from the R console.

This tutorial will demonstrate how to build the workflow in an interactive mode, appending each step. The workflow is constructed by connecting each step via appendStep method. Each SYSargsList instance contains instructions needed for processing a set of input files with a specific command-line or R software and the paths to the corresponding outfiles generated by a particular tool/step.

To create a Workflow within systemPipeR, we can start by defining an empty container and checking the directory structure:

library(systemPipeR)
sal <- SPRproject()
sal

Load packages

This is an empty template that contains only one demo step. Refer to our website for how to add more steps. If you prefer a more enriched template, read this page for other pre-configured templates.

appendStep(sal) <- LineWise(
    code = {
        library(systemPipeR)
    }, 
    step_name = "load_SPR"
)

Version Information

appendStep(sal) <- LineWise(
    code = {
        sessionInfo()
        }, 
    step_name = "sessionInfo", 
    dependency = "load_SPR")

Running workflow

Interactive job submissions in a single machine

For running the workflow, runWF function will execute all the steps store in the workflow container. The execution will be on a single machine without submitting to a queuing system of a computer cluster.

sal <- runWF(sal)

Visualize workflow

systemPipeR workflows instances can be visualized with the plotWF function.

plotWF(sal, rstudio = TRUE)

Checking workflow status

To check the summary of the workflow, we can use:

sal
statusWF(sal)

Accessing logs report

systemPipeR compiles all the workflow execution logs in one central location, making it easier to check any standard output (stdout) or standard error (stderr) for any command-line tools used on the workflow or the R code stdout.

sal <- renderLogs(sal)

References



tgirke/systemPipeRdata documentation built on Oct. 24, 2024, 9:49 p.m.