Assembly and intrahost/low-frequency variant calling for viral samples

Taxonomic classification and profiling of shotgun metagenomic data

Demultiplexing pipeline for Illumina sequencing data

16S rRNA amplicon sequencing analysis workflow using QIIME2.

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The workflow takes a paired-reads collection (like illumina WGS or HiC), runs FastQC and SeqKit, trims with Fastp, and creates a MultiQC report. The main outputs are a paired collection of trimmed reads, a report with raw and trimmed reads stats, and a table with raw reads stats.

The workflow takes a trimmed Illumina WGS paired-end reads collection, Collapsed contigs, and the values for transition parameter and max coverage depth (calculated from WF1) to run Purge_Dups. It produces purged Collapsed contigs assemblies, and runs all the QC analysis (gfastats, BUSCO, and Merqury).

The workflow takes a trimmed Illumina paired-end reads collection, runs Meryl to create a K-mer database, Genomescope2 to estimate genome properties and Smudgeplot to estimate ploidy. The main results are K-mer ddatabase and genome profiling plots, tables, and values useful for downstream analysis. Default K-mer length and ploidy for Genomescope are 21 and 2, respectively.

Workflow (hybrid) metagenomic assembly and binning

• Workflow Illumina Quality: https://workflowhub.eu/workflows/336?version=1
• FastQC (control)
• fastp (quality trimming)
• kraken2 (taxonomy)
• bbmap contamination filter
• Workflow Longread Quality:
• NanoPlot (control)
• filtlong (quality trimming)
• kraken2 (taxonomy)
• minimap2 contamination filter
• Kraken2 taxonomic classification of FASTQ reads
• SPAdes/Flye (Assembly)
• Pilon/Medaka/PyPolCA (Assembly polishing)
• QUAST (Assembly ...

Workflow for Illumina Quality Control and Filtering

Multiple paired datasets will be merged into single paired dataset.

Summary:

• FastQC on raw data files
• fastp for read quality trimming
• BBduk for phiX and (optional) rRNA filtering
• Kraken2 for taxonomic classification of reads (optional)
• BBmap for (contamination) filtering using given references (optional)
• FastQC on filtered (merged) data

Other UNLOCK workflows on WorkflowHub: https://workflowhub.eu/projects/16/workflows?view=default ...

Bootstrapping-for-BQSR @ NCI-Gadi is a pipeline for bootstrapping a variant resource to enable GATK base quality score recalibration (BQSR) for non-model organisms that lack a publicly available variant resource. This implementation is optimised for the National Compute Infrastucture's Gadi HPC. Multiple rounds of bootstrapping can be performed. Users can use Fastq-to-bam @ NCI-Gadi and Germline-ShortV @ NCI-Gadi to ...

RNASeq-DE @ NCI-Gadi processes RNA sequencing data (single, paired and/or multiplexed) for differential expression (raw FASTQ to counts). This pipeline consists of multiple stages and is designed for the National Computational Infrastructure's (NCI) Gadi supercompter, leveraging multiple nodes to run each stage in parallel.

Infrastructure_deployment_metadata: Gadi (NCI)

Flashlite-Trinity contains two workflows that run Trinity on the University of Queensland's HPC, Flashlite. Trinity performs de novo transcriptome assembly of RNA-seq data by combining three independent software modules Inchworm, Chrysalis and Butterfly to process RNA-seq reads. The algorithm can detect isoforms, handle paired-end reads, multiple insert sizes and strandedness. Users can run Flashlite-Trinity on single samples, or smaller samples requiring <500Gb ...