Note: Deprecated as of May 2025. The mRNA preprocessing previously performed by this workflow is now built into the Fgenesh annotation workflow (881) Version 4. This workflow is no longer needed in the TSI annotation pipeline. Please use workflow 881 Version 4 directly with TransDecoder CDS output from workflow 879 (Extract transcripts).

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, ...

Fgenesh Annotation - TSI Workflow Description

Overview

One of a series of workflows to annotate a genome, tagged TSI-annotation. Based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

Workflow Sequence

Run in this order:

• Repeat masking
• RNAseq QC and read trimming
• Find transcripts
• Combine transcripts
• Extract transcripts
• Fgenesh annotation (this workflow)

Inputs Required

Files uploaded by the user:

• assembled_genome.fasta — the ...

Assembly polishing; can run alone or as part of a combined workflow for large genome assembly.

• What it does: Polishes (corrects) an assembly, using long reads (with the tools Racon and Medaka) and short reads (with the tool Racon). (Note: medaka is only for nanopore reads, not PacBio reads).
• Inputs: assembly to be polished: assembly.fasta; long reads - the same set used in the assembly (e.g. may be raw or filtered) fastq.gz format; short reads, R1 only, in fastq.gz format
• Outputs: ...

Germline-ShortV @ NCI-Gadi is an implementation of the BROAD Institute's best practice workflow for germline short variant discovery. This implementation is optimised for the National Compute Infrastucture's Gadi HPC, utilising scatter-gather parallelism to enable use of multiple nodes with high CPU or memory efficiency. This workflow requires sample BAM files, which can be generated using the Fastq-to-bam @ NCI-Gadi pipeline. Germline-ShortV can be applied ...

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:

• 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 ...