Collections

Collection of de-novo genome assembly workflows written for implementation in Galaxy

Input data should be PacBio HiFi reads and Illumina 3-dimensional Chromatin Confirmation Capture (HiC) reads

Executing all workflows will output two, scaffolded, haplotype assemblies

Collection of workflows exploring data in the Image Data Resource (IDR).

This ARDC and BioCommons sponsored project delivers a key component of BioCommon’s vision for an ecosystem of platforms providing researchers with sophisticated data analysis and digital asset stewardship capabilities. The Bring Your Own Data (BYOD) Platform (https://www.biocommons.org.au/byod-expansion) has enabled highly accessible, highly available, highly scalable analysis and data sharing capabilities for the benefit of life science researchers nationally.

**This WorkflowHub collection ...

The Vertebrate Genomes Pipelines in Galaxy are intended to allow a user to generate high-quality near error-free assemblies of species from a user's own data or from the GenomeArk database.

TronFlow is an open source collection of computational workflows originally conceived for tumor-normal somatic variant calling over whole exome data and the manipulation of BAM and VCF files with the aim of having comparable and analysis-ready data. Over time, we have extended it to germline variant calling, copy numbers and other related technologies and analyses.

Its modular architecture covers different analytical and methodological use cases that allow analysing FASTQ files into analysis-ready ...

Selection of BioExcel Building Blocks (BioBB) Workflows, across three workflow languages (jupyter notebooks, CWL, and Galaxy), demonstrating the use of BioBB tool descriptors for each of these systems.

Selection of BioExcel Building Blocks (BioBB) Workflows intended for tutorials and training.

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data. Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, ...