Workflows
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A comprehensive Galaxy workflow for the end-to-end analysis of transcriptomics data, featuring automated QC, clustering, spatial statistics, cell type annotation, and cell-cell communication.
Type: Galaxy
Creators: Amirhossein Naghsh Nilchi, Pavankumar Videm, Björn Grüning
Submitter: Amirhossein Naghsh Nilchi
This workflow was built for the 2024 Bioinformatics Bootcamp at The Open University. It is meant to occur after the (universal) Filter, plot and explore tutorial to allow analysis of a single cluster.
This workflow was developed for the 2024 Bioinformatics Bootcamp at The Open University. It imports datasets from the EBI SCXA, reformats then, and analyses them similar to the Filter, plot and explore Galaxy tutorial.
Type: Galaxy
Creators: Wendi Bacon, Julia Jakiela, The Open University
Submitter: Diana Chiang Jurado
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
- annotates them using the ENSEMBL Variant Effect Predictor and custom annotation data
- turns the annotated VCF into a MAF file for import into cBioPortal
- generates human-readable variant- and gene-centric ...