Within the GHGA workflow workstream, our bioinformatics team is making steady progress in our effort to provide standardized, comparable, and reproducible omics workflows for the research community. To streamline workflows, the team is improving existing workflows (instead of creating a new process) and aligning with the nf-core community, curating best practice analytic pipelines. Below, we highlight workflow releases GHGA has been involved in.
If you are starting to use nf-core workflows, we recomment Bytesize - a video tutorial series published by nf-core that covers workflow implementation and nf-core workflows in short and easy to follow snippets!
Continuous benchmarking against known standards is essential to ensure precision and reliability in variant calling tools and workflows. A recent publication, spearheaded by the Next Generation Sequencing Competence Network (NGS-CN) and GHGA, introduces NCBench, a platform for continuous benchmarking of genomic variant calling workflows. NCBench provides a comprehensive and reproducible benchmarking workflow for the evaluation of small genomic variant callsets in terms of recall, precision, and error patterns. Its continuous and open-source approach eliminates the need for specialised infrastructure, making benchmarking accessible and transparent to the research and diagnostics community but also to patients.
Somatic and germline variant calling pipeline from nf-core - GHGA is developing and testing a coordinated guide and config for the harmonized calling of variants given public resources and tool settings.
Learn moreTool for long-read sequencing which focuses on the Oxford Nanopore technology from nf-core - GHGA is developing and testing a coordinated guide and config for harmonized long-read alignment and QC.
Learn moreThe Detection of RNA Outliers Pipeline (DROP) is a Snakemake pipeline - A tool for RNA-seq processing and interpretation of rare disease outlier detection, that guides researchers toward aberrant RNA events (splicing and expression).
Learn moreNextflow-based pipeline to call and prioritize somatic indels with extensive quality control and filtering steps. Redeveloped from the original roddy pipeline used in Pan-cancer analysis of whole genomes study.
Learn moreNextflow pipeline to call and prioritize somatic single nucleotide variations with filtering, annotations, and plots. Redeveloped from the original roddy pipeline used in Pan-cancer analysis of whole genomes study.
Learn moreNextflow pipeline to estimate allele-specific copy numbers from human Whole Genome Sequencing data (>30X). Redeveloped from the original roddy pipeline used in Pan-cancer analysis of whole genomes study.
Learn moreRNA sequencing data analysis pipeline from nf-core - GHGA is developing and testing a coordinated guide and config for harmonized RNA-seq analysis and gene expression estimation given public resources and tool settings.
Learn more10X Genomics single-cell RNA sequencing data analysis pipeline from nf-core - GHGA is developing and testing a coordinated guide and config for harmonized single-cell data analysis and gene expression estimation given public resources and tool settings.
Learn moreVariant benchmarking pipeline for germline and somatic variant callers - GHGA is the main developer of this nf-core pipeline.
Learn moreBest practice preprocessing and quality control pipeline for Xenium data for in situ spatial profiling - GHGA is the main developer of this nf-core pipeline.
Learn moreBest practice quality control pipeline for short- and long-read sequencing data. This pipeline will be used in model project GenomSeq.
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