KINC-nf

The Nextflow pipeline for KINC.

Dependencies

All you need is nextflow, Docker, and nvidia-docker. On HPC systems, you can use Singularity in lieu of Docker. If for some reason you can't use either container software, you will have to install KINC from source.

Installation

You don't. But you may want to refer to the config file on GitHub file and familiarize yourself with the available settings.

Usage

You can run the pipeline out-of-the-box with Nextflow. We also provide some example data to get you started. Here's how to run KINC on the example data:

nextflow run systemsgenetics/kinc-nf -profile example,<docker|singularity>

This example will download the pipeline repository, the example data, and the Docker/Singularity container for KINC, and run KINC on the example data. The results will be saved to ./output.

KINC-nf detects input files by their file extension. For example, the default extension for GEM files is *.emx.txt, so make sure that your input GEMs have this extension before running the pipeline. You can also place intermediate files in the input directory, and KINC-nf will use them as inputs to the appropriate processes. For example, you can provide the *.emx file created by import_emx instead of the plain-text GEM and KINC-nf will skip the import_emx step.

You can specify any of the params in nextflow.config as command-line arguments, for example:

nextflow run systemsgenetics/kinc-nf \
    --similarity_chunks 1 \
    --similarity_hardware_type gpu

The params allow you to control which analytics to run, how many chunks to use where applicable, and various other command-line parameters for KINC. You can resume a failed run with the -resume flag. Consult the Nextflow documentation for more information on these and other options.

Palmetto

To run KINC-nf on Palmetto, you have to use Singularity instead of Docker, and use the palmetto profile:

nextflow run systemsgenetics/kinc-nf -profile palmetto,singularity

Kubernetes

You can run this pipeline, as well as any other nextflow pipeline, on a Kubernetes cluster with minimal effort. Consult the kube-runner repo for instructions.