A porting of the Trinity RNA assembly pipeline, https://trinityrnaseq.github.io, that uses Nextflow to handle the underlying sub-tasks.
This enables additional capabilities to better use HPC resources, such as packing of tasks to fill up nodes and use of node-local disks to improve I/O.
By design, the pipeline separates the workflow logic (main file) and the cluster-specific configuration (config files), improving portability.
Based on a pipeline by Sydney Informatics Hub:
Rare disease researchers workflow is that they submit their raw data (fastq), run the mapping and variant calling RD-Connect pipeline and obtain unannotated gvcf files to further submit to the RD-Connect GPAP or analyse on their own.
This demonstrator focuses on the variant calling pipeline. The raw genomic data is processed using the RD-Connect pipeline (Laurie et al., 2016) running on the standards (GA4GH) compliant, interoperable container
A workflow for mapping and consensus generation of SARS-CoV2 whole genome amplicon nanopore data implemented in the Nextflow framework. Reads are mapped to a reference genome using Minimap2 after trimming the amplicon primers with a fixed length at both ends of the amplicons using Cutadapt. The consensus is called using Pysam based on a majority read support threshold per position of the Minimap2 alignment and positions with less than 30x coverage are masked using ‘N’.
Creator: David F. Nieuwenhuijse, Alexey Sokolov
Submitter: Ross Thorne
metaboigniter is bioinformatics pipeline for pre-processing of mass spectrometry-based metabolomics data. It can be used to perform quantification and identification based on MS1 and MS2 data. The backbone of pipeline is based on XCMS, OpenMS, CAMERA, MSnbase, MetFrag, CSIFingerID, CFM-ID, and several other customized tools to noise filtering, quantification and identification both for library and in-silico identification. Please go on to this page to learn how to use the workflow
Creator: Payam Emami
Submitter: Phil Ewels