Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational biological research.
- Accessible: Users can easily run tools without writing code or using the CLI; all via a user-friendly web interface.
- Reproducible: Galaxy captures all the metadata from an analysis, making it completely reproducible.
- Transparent: Users share and publish analyses via interactive pages that can enhance analyses with user annotations.
- Scalable: Galaxy can run on anything, from a laptop, to large clusters, to the cloud
Space: Australian BioCommons
SEEK ID: https://workflowhub.eu/projects/54
Public web page: https://usegalaxy.org.au/
Organisms: No Organisms specified
WorkflowHub PALs: No PALs for this Team
Team created: 9th Aug 2021
Related items
Teams: Australian BioCommons, Galaxy Australia, ELIXIR Training, ELIXIR Tools platform
Organizations: University of Melbourne, Australian BioCommons
https://orcid.org/0000-0002-2977-5032Expertise: Biochemistry, Proteomics, Mass Spectrometry Imaging
Tools: Mass spectrometry, Proteomics
Teams: QCIF Bioinformatics, Galaxy Australia
Organizations: QCIF
https://orcid.org/0000-0003-2439-8650Teams: Galaxy Australia, QCIF Bioinformatics
Organizations: QCIF
https://orcid.org/0000-0002-1480-3563The 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
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
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 ...
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 = masked_genome.fasta and table of repeats found.
...
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
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 ...
Type: Galaxy
Creators: Gareth Price, Anna Syme, Gareth Price, Anna Syme
Submitters: Johan Gustafsson, Anna Syme
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) ...
workflow-partial-gstacks-populations
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
This workflow is part of the reference-guided stacks workflow, https://workflowhub.eu/workflows/347
This workflow takes in bam files and a population map.
To generate bam files see: https://workflowhub.eu/workflows/351
workflow-partial-bwa-mem
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
This workflow is part of the reference-guided stacks workflow, https://workflowhub.eu/workflows/347
Inputs
- demultiplexed reads in fastq format, may be output from the QC workflow. Files are in a collection.
- reference genome in fasta format ...
workflow-partial-cstacks-sstacks-gstacks
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
This workflow takes in ustacks output, and runs cstacks, sstacks and gstacks.
To generate ustacks output see https://workflowhub.eu/workflows/349
For the full de novo workflow see https://workflowhub.eu/workflows/348
workflow-partial-ustacks-only
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
For the full de novo workflow see https://workflowhub.eu/workflows/348
You may want to run ustacks with different batches of samples.
- To be able to combine these later, there are some necessary steps - we need to keep track of how many ...
workflow-denovo-stacks
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
Inputs
- demultiplexed reads in fastq format, may be output from the QC workflow. Files are in a collection.
- population map in text format
Steps and outputs
ustacks:
- input reads go to ustacks.
- ustacks assembles the reads into matching ...
workflow-ref-guided-stacks
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
Inputs
- demultiplexed reads in fastq format, may be output from the QC workflow. Files are in a collection.
- population map in text format
- reference genome in fasta format
Steps and outputs
BWA MEM 2:
- The reads are mapped to the ...
workflow-qc-of-radseq-reads
These workflows are part of a set designed to work for RAD-seq data on the Galaxy platform, using the tools from the Stacks program.
Galaxy Australia: https://usegalaxy.org.au/
Stacks: http://catchenlab.life.illinois.edu/stacks/
Inputs
- demultiplexed reads in fastq format, in a collection
- two adapter sequences in fasta format, for input into cutadapt
Steps and outputs
The workflow can be modified to suit your own parameters.
The workflow steps are:
- Run ...
Combined workflow for large genome assembly
The tutorial document for this workflow is here: https://doi.org/10.5281/zenodo.5655813
What it does: A workflow for genome assembly, containing subworkflows:
- Data QC
- Kmer counting
- Trim and filter reads
- Assembly with Flye
- Assembly polishing
- Assess genome quality
Inputs:
- long reads and short reads in fastq format
- reference genome for Quast
Outputs:
- Data information - QC, kmers
- Filtered, trimmed reads
- Genome assembly, assembly graph, ...
Assess genome quality; can run alone or as part of a combined workflow for large genome assembly.
- What it does: Assesses the quality of the genome assembly: generate some statistics and determine if expected genes are present; align contigs to a reference genome.
- Inputs: polished assembly; reference_genome.fasta (e.g. of a closely-related species, if available).
- Outputs: Busco table of genes found; Quast HTML report, and link to Icarus contigs browser, showing contigs aligned to a reference ...
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