Australian BioCommons
OverviewThe 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.
Space: Australian BioCommons
SEEK ID: https://workflowhub.eu/projects/30
Public web page: https://www.biocommons.org.au/
Organisms: No Organisms specified
WorkflowHub PALs: No PALs for this Team
Team created: 16th Feb 2021
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Teams: Australian BioCommons
Organizations: Australian BioCommons
https://orcid.org/0000-0002-4032-5331
Teams: Australian BioCommons
Organizations: Australian BioCommons
https://orcid.org/0000-0002-7396-5757
Teams: Australian BioCommons
Organizations: University of Melbourne, Australian BioCommons
https://orcid.org/0000-0001-8198-9735
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.
Teams: Australian BioCommons, QCIF Bioinformatics, Pawsey Supercomputing Research Centre, Sydney Informatics Hub, Janis, Melbourne Data Analytics Platform (MDAP), Galaxy Australia, National Computational Infrastructure (NCI) WorkflowHub team
Web page: https://www.biocommons.org.au/
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.
Type: Nextflow
Creators: Nandan Deshpande, Tracy Chew, Cali Willet, Georgina Samaha
Submitter: Georgina Samaha
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, ...
Type: Nextflow
Creators: Georgina Samaha, Marina Kennerson, Tracy Chew, Sarah Beecroft
Submitter: Georgina Samaha
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 ...
Type: Nextflow
Creators: Naga Kasinadhuni, Ziad Al-Bkhetan, Martha Zakrzewski, Kenneth Chan, Uwe Winter, Johan Gustafsson
Submitter: Johan Gustafsson
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
===========
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 ...
Type: Shell Script
Creators: Cali Willet, Tracy Chew, Georgina Samaha, Rosemarie Sadsad, Andrey Bliznyuk, Ben Menadue, Rika Kobayashi, Matthew Downton, Yue Sun
Submitter: Georgina Samaha
Download
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 ...
