Last updated: 2020-05-23

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Knit directory: bioinformatics_tips/

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Rmd 3a4d719 davetang 2020-05-23 Workflow management system

A bioinformatics analysis typically requires multiple sequential steps, where the output of one analysis becomes the input of the next; this is typically called a “bioinformatics pipeline”. There are various ways to implement bioinformatics pipelines; you can simply set up various scripts and have them run one after the another. There is nothing wrong with this approach but using a workflow management system will make your life much easier.

Workflow management systems will typically handle logging, resource management, and execution of your pipeline. A very popular option is Snakemake and are made up of rules.

rule sort:
    input:
        "test.txt"
    output:
        "test.sorted.txt"
    shell:
        "sort -n {input} > {output}"

If we run the example above using Snakemake, the input file test.txt will get sorted numerically and the output is stored in test.sorted.txt. Typically, you would write a pipeline (a Snakefile) that takes input from a config file (e.g. config.yaml). If you wanted to run the pipeline for a new dataset, you will just need to create a new config file.

Other workflow management systems include Bpipe and Nextflow, which both are based on Groovy. A survey conducted on Twitter has a list of other systems and showed that Snakemake is the most popular. Personally I use the Workflow Description Language because that’s what the Broad Institute uses and I wanted to use some of their pipelines. There is a nice discussion on Reddit on the strengths and weakness of different workflow management systems.

Bottom line is that you should write your bioinformatics pipelines using a workflow management system. Chances are that somebody has already implemented a similar pipeline using a workflow management system.


sessionInfo()
R version 4.0.0 (2020-04-24)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.4

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_1.6.2

loaded via a namespace (and not attached):
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[21] yaml_2.2.1      compiler_4.0.0  htmltools_0.4.0 knitr_1.28