A community effort to collect a curated set of analysis pipelines built using Nextflow.

IWC - Intergalactic Workflow Commission

The Vertebrate Genomes Pipelines in Galaxy are intended to allow a user to generate high-quality near error-free assemblies of species from a user's own data or from the GenomeArk database

Workflow for variant analysis against a reference genome in GenBank format

Single-cell/nuclei pipeline for data derived from Oxford Nanopore

Scaffolding using HiC data with YAHS.

Pipeline to run and benchmark multiple sequence alignment tools.

Clinical Metaproteomics 4: Quantitation

Find and annotate variants in ampliconic SARS-CoV-2 Illumina sequencing data and classify samples with pangolin and nextclade

This workflow takes a VCF dataset of variants produced by any of the *-variant-calling workflows in https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling and generates tabular lists of variants by Samples and by Variant, and an overview plot of variants and their allele-frequencies.

COVID-19: variation analysis on ARTIC PE data

The workflow for Illumina-sequenced ampliconic data builds on the RNASeq workflow for paired-end data using the same steps for mapping and variant calling, but adds extra logic for trimming amplicon primer sequences off reads with the ivar package. In addition, this workflow uses ivar also to identify amplicons affected by primer-binding site mutations and, if possible, excludes reads derived from such ...

Assembly of bacterial paired-end short read data with generation of quality metrics and reports

Short paired-end read analysis to provide quality analysis, read cleaning and taxonomy assignation

Pairwise alignment pipeline (genome to genome or reads to genome)

Purge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication). This workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)

Scaffolding with Bionano

Scaffolding using Bionano optical map data

Inputs

1. Bionano data [cmap]
2. Estimated genome size [txt]
3. Phased assembly generated by Hifiasm [gfa1]

Outputs

1. Scaffolds
2. Non-scaffolded contigs
3. QC: Assembly statistics
4. QC: Nx plot
5. QC: Size plot

Purge Duplicate Contigs

Purge contigs marked as duplicates by purge_dups in a single haplotype(could be haplotypic duplication or overlap duplication) This workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)

Inputs

1. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)
2. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)
3. Assembly to purge (e.g. hap1) ...

Contiging Solo:

Generate assembly based on PacBio Hifi Reads.

Inputs

1. Hifi long reads [fastq]
2. K-mer database [meryldb]
3. Genome profile summary generated by Genomescope [txt]
4. Homozygous Read Coverage. Optional, use if you think the estimation from Genomescope is inacurate.
5. Genomescope Model Parameters generated by Genomescope [tabular]
6. Database for busco lineage (recommended: latest)
7. Busco lineage (recommended: vertebrata)
8. Name of first assembly
9. Name of second ...

Assembly with Hifi reads and Trio Data

Generate phased assembly based on PacBio Hifi Reads using parental Illumina data for phasing

Inputs

1. Hifi long reads [fastq]
2. Concatenated Illumina reads : Paternal [fastq]
3. Concatenated Illumina reads : Maternal [fastq]
4. K-mer database [meryldb]
5. Paternal hapmer database [meryldb]
6. Maternal hapmer database [meryldb]
7. Genome profile summary generated by Genomescope [txt]
8. Genome model parameters generated by Genomescope [tabular]

...

A pipeline for de novo transcriptome assembly of short reads from bulk RNA-seq

Create Meryl Database used for the estimation of assembly parameters and quality control with Merqury. Part of the VGP pipeline.

VGP Workflow #1

This workflow produces a Meryl database and Genomescope outputs that will be used to determine parameters for following workflows, and assess the quality of genome assemblies. Specifically, it provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality.

Inputs

• A collection of Hifi long reads in FASTQ format
• k-mer length
• Ploidy

Outputs

• Meryl Database of kmer counts

...