The Australian BioCommons enhances digital life science research through world class collaborative distributed infrastructure. It aims to ensure that Australian life science research remains globally competitive, through sustained strategic leadership, research community engagement, digital service provision, training and support.

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

Inputs required: assembled-genome.fasta, hard-repeat-masked-genome.fasta, and (because this workflow maps known mRNA ...

Genome assembly workflow for nanopore reads, for TSI

Input:

• Nanopore reads (can be in format: fastq, fastq.gz, fastqsanger, or fastqsanger.gz)

Optional settings to specify when the workflow is run:

• [1] how many input files to split the original input into (to speed up the workflow). default = 0. example: set to 2000 to split a 60 GB read file into 2000 files of ~ 30 MB.
• [2] filtering: min average read quality score. default = 10
• [3] filtering: min read length. default = 200
• [4] ...

Scaffolding using HiC data with YAHS

This workflow has been created from a Vertebrate Genomes Project (VGP) scaffolding workflow.

• For more information about the VGP project see https://galaxyproject.org/projects/vgp/.
• The scaffolding workflow is at https://dockstore.org/workflows/github.com/iwc-workflows/Scaffolding-HiC-VGP8/main:main?tab=info
• Please see that link for the workflow diagram.

Some minor changes have been made to better fit with TSI project data:

• optional inputs of SAK info ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

Workflow information:

• Input = genome.fasta.
• Outputs = soft_masked_genome.fasta, hard_masked_genome.fasta, ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

About this workflow:

• Inputs: transdecoder-peptides.fasta, transdecoder-nucleotides.fasta
• Runs many steps ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

About this workflow:

• Input: merged_transcriptomes.fasta.
• Runs TransDecoder to produce longest_transcripts.fasta ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

About this workflow:

• Inputs: multiple transcriptome.gtfs from different tissues, genome.fasta, coding_seqs.fasta, ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

About this workflow:

• Run this workflow per tissue.
• Inputs: masked_genome.fasta and the trimmed RNAseq reads ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

About this workflow:

• Repeat this workflow separately for datasets from different tissues.
• Inputs = collections ...

Post-genome assembly quality control workflow using Quast, BUSCO, Meryl, Merqury and Fasta Statistics. Updates November 2023. Inputs: reads as fastqsanger.gz (not fastq.gz), and assembly.fasta. New default settings for BUSCO: lineage = eukaryota; for Quast: lineage = eukaryotes, genome = large. Reports assembly stats into a table called metrics.tsv, including selected metrics from Fasta Stats, and read coverage; reports BUSCO versions and dependencies; and displays these tables in the workflow ...

Welcome to the pipesnake. Let's get started.

Introduction

pipesnake is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity ...

This is a Nextflow implementaion of the GATK Somatic Short Variant Calling workflow. This workflow can be used to discover somatic short variants (SNVs and indels) from tumour and matched normal BAM files following GATK's Best Practices Workflow. The workflowis currently optimised to run efficiently and at scale on the National Compute Infrastructure, Gadi.

GermlineStructuralV-nf is a pipeline for identifying structural variant events in human Illumina short read whole genome sequence data. GermlineStructuralV-nf identifies structural variant and copy number events from BAM files using Manta, Smoove, and TIDDIT. Variants are then merged using SURVIVOR, ...

HiFi de novo genome assembly workflow

HiFi-assembly-workflow is a bioinformatics pipeline that can be used to analyse Pacbio CCS reads for de novo genome assembly using PacBio Circular Consensus Sequencing (CCS) reads. This workflow is implemented in Nextflow and has 3 major sections.

Please refer to the following documentation for detailed description of each workflow section:

• [Adapter filtration and pre-assembly quality control ...

IGVreport-nf

• Description
• Diagram
• User guide
• Workflow summaries
• Metadata
• Component tools
• Required (minimum) inputs/parameters
• Additional notes
• Help/FAQ/Troubleshooting
• Acknowledgements/citations/credits

Description

Quickly generate [IGV .html ...

PacBio HiFi genome assembly using hifiasm v2.1

General usage recommendations

Please see the Genome assembly with hifiasm on Galaxy Australia guide.

See change log

Acknowledgements

The workflow & the doc_guidelines template used are supported by the Australian BioCommons via Bioplatforms Australia funding, the Australian ...

Purge-duplicates-from-hifiasm-assembly

General recommendations for using Purge-duplicates-from-hifiasm-assembly

Please see the Genome assembly with hifiasm on Galaxy Australia guide.

Acknowledgements

The workflow & the doc_guidelines template used are supported by the Australian BioCommons via Bioplatforms Australia funding, the Australian ...

BAM-to-FASTQ-QC

General recommendations for using BAM-to-FASTQ-QC

Please see the Genome assembly with hifiasm on Galaxy Australia guide.

Acknowledgements

The workflow & the doc_guidelines template used are supported by the Australian BioCommons via Bioplatforms Australia funding, the Australian Research Data Commons (https://doi.org/10.47486/PL105) ...

IndexReferenceFasta-nf

===========

• Description
• Diagram
• User guide
• Benchmarking
• Workflow summaries
• Metadata
• Component tools
• Required (minimum) inputs/parameters
• Additional notes
• Help/FAQ/Troubleshooting
• Acknowledgements/citations/credits ...

Fastq-to-BAM @ NCI-Gadi is a genome alignment workflow that takes raw FASTQ files, aligns them to a reference genome and outputs analysis ready BAM files. This workflow is designed for the National Computational Infrastructure's (NCI) Gadi supercompter, leveraging multiple nodes on NCI Gadi to run all stages of the workflow in parallel, either massively parallel using the scatter-gather approach or parallel by sample. It consists of a number of stages and follows the BROAD Institute's best practice ...

This is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Convert formats
• Fgenesh annotation

This ARDC and BioCommons sponsored project delivers a key component of BioCommon’s vision for an ecosystem of platforms providing researchers with sophisticated data analysis and digital asset stewardship capabilities. The Bring Your Own Data (BYOD) Platform (https://www.biocommons.org.au/byod-expansion) has enabled highly accessible, highly available, highly scalable analysis and data sharing capabilities for the benefit of life science researchers nationally.

**This WorkflowHub collection ...