Subset data on the Mediterreanean see and extract and visualise the Phosphate variable

Process argo data with the Pangeo Ecosystem and visualise them with Ocean Data View (ODV)

Secondary metabolite biosynthetic gene cluster (SMBGC) Annotation using Neural Networks Trained on Interpro Signatures

This workflow takes a cell-type-annotated AnnData object (processed with SnapATAC2) and performs peak calling with MACS3 on the cell types. Next, a cell-by-peak matrix is constructed and differential accessibility tests are performed for comparison of either two cell types or one cell type with a background of all other cells. Lastly, differentially accessible marker regions for each cell type are identified.

This Workflow takes a dataset collection of single-cell ATAC-seq fragments and performs:

• preprocessing
• filtering
• concatenation
• dimension reduction
• batch correction (with Harmony and optionally Scanorama and MNC-correct)
• leiden clustering

• new SnapATAC2 version: from 2.5.3 to 2.6.4

Workflow for Single-cell ATAC-seq standard processing with SnapATAC2. This workflow takes a fragment file as input and performs the standard steps of scATAC-seq analysis: filtering, dimension reduction, embedding and visualization of marker genes with SnapATAC2. Finally, the clusters are manually annotated with the help of marker genes. In an alternative step, the fragment file can also be generated from a BAM file.

• newer Version: Updated SnapATAC2 version from 2.5.3 to 2.6.4

A variation of the Cancer variant annotation (hg38 VEP-based) workflow at https://doi.org/10.48546/workflowhub.workflow.607.1.

Like that other workflow it takes a list of tumor/normal sample pair variants in VCF format (see the other workflow for details about the expected format) and

1. annotates them using the ENSEMBL Variant Effect Predictor and custom annotation data
2. turns the annotated VCF into a MAF file for import into cBioPortal
3. generates human-readable variant- and gene-centric ...

Call somatic, germline and LoH event variants from PE Illumina sequencing data obtained from matched pairs of tumor and normal tissue samples.

This workflow can be used with whole-genome and whole-exome sequencing data as input. For WES data, parts of the analysis can be restricted to the exome capture kits target regions by providing the optional "Regions of Interest" bed dataset.

The current version uses bwa-mem for read mapping and varscan somatic for variant calling and somatic status ...

This Galaxy workflow takes a list of tumor/normal sample pair variants in VCF format and

1. annotates them using the ENSEMBL Variant Effect Predictor and custom annotation data
2. turns the annotated VCF into a MAF file for import into cBioPortal
3. generates human-readable variant- and gene-centric reports

The input VCF is expected to encode somatic status, somatic p-value and germline p-value of each variant in varscan somatic format, i.e., via SS, SPV and GPV INFO keys, respectively.

Generic consensus building

This workflow generates consensus sequences using a list of variants generated by Variant Calling Workflow.

The workflow accepts a single input:

• A collection of VCF files

The workflow produces a single output:

• Consensus sequence for each input VCF file

The workflow can be accessed at usegalaxy.org