Loads a single cell counts matrix into an annData format - adding a column called sample with the sample name. (Input format - matrix.mtx, features.tsv and barcodes.tsv)

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 ...

Parabricks-Genomics-nf is a GPU-enabled pipeline for alignment and germline short variant calling for short read sequencing data. The pipeline utilises NVIDIA's Clara Parabricks toolkit to dramatically speed up the execution of best practice bioinformatics tools. Currently, this pipeline is configured specifically for NCI's Gadi HPC.

NVIDIA's Clara Parabricks can deliver a significant ...

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.