nf-core/deepmodeloptim
Stochastic Testing and Input Manipulation for Unbiased Learning Systems
artificial-intelligencedataprocessingdeeplearninggenomicslarge-scaleoptimizationprototyping-tool
This is the development version of the pipeline.
Launch development version https://github.com/nf-core/deepmodeloptim Introduction
This document describes the output produced by the pipeline.
The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.
Pipeline overview
The pipeline is built using Nextflow and processes data using the following steps:
- Pipeline information - Report metrics generated during the workflow execution
Pipeline information
Output files
pipeline_info/- Reports generated by Nextflow:
execution_report.html,execution_timeline.html,execution_trace.txtandpipeline_dag.dot/pipeline_dag.svg. - Reports generated by the pipeline:
pipeline_report.html,pipeline_report.txtandsoftware_versions.yml. Thepipeline_report*files will only be present if the--email/--email_on_failparameter’s are used when running the pipeline. - Reformatted samplesheet files used as input to the pipeline:
samplesheet.valid.csv. - Parameters used by the pipeline run:
params.json.
- Reports generated by Nextflow:
Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.