A space managed by WorkflowHub administrators for teams that don't want/need to manage their own space.
Teams: IBISBA Workflows, NMR Workflow, UNLOCK, NanoGalaxy, Galaxy Climate, PNDB, IMBforge, COVID-19 PubSeq: Public SARS-CoV-2 Sequence Resource, LBI-RUD, Nick-test-team, usegalaxy-eu, Italy-Covid-data-Portal, UX trial team, Integrated and Urban Plant Pathology Laboratory, SARS-CoV-2 Data Hubs, lmjxteam2, virAnnot pipeline, Ay Lab, iPC: individualizedPaediatricCure, Harkany Lab, MOLGENIS, EJPRD WP13 case-studies workflows, Common Workflow Language (CWL) community, Testing, SeBiMER, IAA-CSIC, MAB - ATGC, Probabilistic graphical models, GenX, Snakemake-Workflows, ODA, IPK BIT, CO2MICS Lab, FAME, CHU Limoges - UF9481 Bioinformatique / CNR Herpesvirus, Quadram Institute Bioscience - Bioinformatics, HecatombDevelopment, Institute of Human Genetics, Testing RO Crates, Test Team, Applied Computational Biology at IEG/HMGU, INFRAFRONTIER workflows, OME, TransBioNet, OpenEBench, Bioinformatics and Biostatistics (BIO2 ) Core, VIB Bioinformatics Core, CRC Cohort, ICAN, MustafaVoh, Single Cell Unit, CO-Graph, emo-bon, TestEMBL-EBIOntology, CINECA, Toxicology community, Pitagora-Network, Workflows Australia, Medizinisches Proteom-Center, Medical Bioinformatics, AGRF BIO, EU-Openscreen, X-omics, ELIXIR Belgium, URGI, Size Inc, GA-VirReport Team, The Boucher Lab, Air Quality Prediction, pyiron, CAPSID, Edinburgh Genomics, Defragmentation TS, NBIS, Phytoplankton Analysis, Seq4AMR, Workflow registry test, Read2Map, SKM3, ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression, de.NBI Cloud, Meta-NanoSim, ILVO Plant Health, EMERGEN-BIOINFO, KircherLab, Apis-wings, BCCM_ULC, Dessimoz Lab, TRON gGmbH, GEMS at MLZ, Computational Science at HZDR, Big data in biomedicine, TRE-FX, MISTIC, Guigó lab, Statistical genetics, Delineating Regions-of-interest for Mass Spectrometry Imaging by Multimodally Corroborated Spatial Segmentation, OLCF-WES, Bioinformatics Unit @ CRG, Bioinformatics Innovation Lab, BSC-CES, ELIXIR Proteomics, Black Ochre Data Labs, Zavolan Lab, Metabolomics-Reproducibility, Team Cardio, NGFF Tools, Bioinformatics workflows for life science, Workflows for geographic science, Pacific-deep-sea-sponges-microbiome, CSFG, SNAKE, Katdetectr, INFRAFRONTIER GmbH, PerMedCoE, Euro-BioImaging, EOSC-Life WP3 OC Team, cross RI project, ANSES-Ploufragan, SANBI Pathogen Bioinformatics, Biodata Analysis Group, DeSci Labs, Erasmus MC - Viroscience Bioinformatics, ARA-dev, Mendel Centre for Plant Genomics and Proteomics, Metagenomic tools, WorkflowEng, Polygenic Score Catalog, bpm, scNTImpute, Systems Biotechnology laboratory, Cimorgh IT solutions, MLme: Machine Learning Made Easy, Hurwitz Lab, Dioscuri TDA, Scipion CNB, System Biotechnology laboratory, yPublish - Bioinfo tools, NIH CFDE Playbook Workflow Partnership, MMV-Lab, EMBL-CBA, EBP-Nor, Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data, Bioinformatics Laboratory for Genomics and Biodiversity (LBGB), multi-analysis dFC, CholGen, RNA group, Plant Genomes Pipelines in Galaxy, Pathogen Genomic Laboratory, Chemical Data Lab, JiangLab, Pangenome database project, HP2NET - Framework for construction of phylogenetic networks on High Performance Computing (HPC) environment, Center for Open Bioimage Analysis, Generalized Open-Source Workflows for Atomistic Molecular Dynamics Simulations of Viral Helicases, Historical DNA genome skimming, QCDIS, Peter Menzel's Team, NHM Clark group, ESRF Workflow System (Ewoks), Kalbe Bioinformatics, Nextflow4Metabolomics, GBCS, CEMCOF, Jackson Laboratory NGS-Ops, Schwartz Lab, BRAIN - Biomedical Research on Adult Intracranial Neoplasms, Cancer Therapeutics and Drug Safety, Deepdefense, Mid-Ohio Regional Planning Commission, MGSSB, Institute for Human Genetics and Genomic Medicine Aachen, FengTaoSMU, EGA, Plant-Food-Research-Open, KrauthammerLab, Geo Workflows, grassland pDT, FunGIALab, CRIM - Computer Research Institute of Montréal, Medvedeva Lab, Metagenlab, FAIR-EASE, Protein-protein and protein-nucleic acid binding site prediction research, Culhane Lab, IDUN - Drug Delivery and Sensing, Edge Computing DAG Task Scheduling Research Group, Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a non-invasive tool for skin barrier assessment, COPO, Taudière group, ErasmusMC Clinical Bioinformatics, interTwin, fluid flow modeling, EnrichDO, WorkflowResearch, Application Security - Test Crypt4GH solutions, RenLabBioinformatics, Yongxin's team, PiFlow, HLee_SeoGroup, UFZ - Image Data Management and Processing Workflows, Korean Bioinformaticians, Into the deep, XChem
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The Galaxy Training Network (GTN) is a collection of hands-on tutorials that are designed to be interactive and are built around Galaxy.
These tutorials can be used for learning and teaching how to use Galaxy for general data analysis, as well as a wide array of hands-on tutorials covering specific domains such as assembly, RNA-Seq analysis, deep learning, climate analysis, and more!
This collection houses some scanpy-based scRNAseq workflows on galaxy Australia.
The aim of these workflows is to handle the routine ‘boring’ part of single cell RNAseq data processing. It will produces an ‘AnnData’ object, which can then be used as a base for downstream analysis – either within galaxy or outside of it. AnnData is a standard format used by the ‘scanpy’ python package.
These workflows represent just one way of processing data for a ‘typical’ scRNAseq experiment – there are many ...
This is part of a series of workflows to annotate a genome, tagged with TSI-annotation.
These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.
The workflows can be run in this order:
- Repeat masking
- RNAseq QC and read trimming
- Find transcripts
- Combine transcripts
- Extract transcripts
- Convert formats
- Fgenesh annotation
RNAseq workflow UMG: Here we introduce a scientific workflow implementing several open-source software executed by Galaxy parallel scripting language in an high-performance computing environment. We have applied the workflow to a single-cardiomyocyte RNA-seq data retrieved from Gene Expression Omnibus database. The workflow allows for the analysis (alignment, QC, sort and count reads, statistics generation) of raw RNA-seq data and seamless integration of differential expression results into a ...
Analyse Bulk RNA-Seq data in preparation for downstream Pathways analysis with MINERVA
Analyse Bulk RNA-Seq data in preparation for downstream Pathways analysis with MINERVA
Type: Galaxy
Creators: Iacopo Cristoferi, Helena Rasche, Clinical Bioinformatics Unit, Pathology Department, Eramus Medical Center
Submitter: Helena Rasche
Genome-wide alternative splicing analysis v.2
This is part of a series of workflows to annotate a genome, tagged with TSI-annotation.
These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.
The workflows can be run in this order:
- Repeat masking
- RNAseq QC and read trimming
- Find transcripts
- Combine transcripts
- Extract transcripts
- Convert formats
- Fgenesh annotation
About this workflow:
- Repeat this workflow separately for datasets from different tissues.
- Inputs = collections ...
This workflow correspond to the Genome-wide alternative splicing analysis training. It allows to analyze isoform switching by making use of IsoformSwitchAnalyzeR.
Abstract CWL Automatically generated from the Galaxy workflow file: Copy of Genome-wide alternative splicing analysis
Tests This workflow can only work on an experimental setup with exactly 2 conditions. It takes two collections of count tables as input and performs differential expression analysis. Additionally it filters for DE genes based on adjusted p-value and log2 fold changes thresholds. It also generates informative plots.
This workflow takes as input a list of single-read fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously. The counts are reprocess to be similar to HTSeq-count output. FPKM are computed with cufflinks. Coverage (per million mapped reads) are computed with bedtools on uniquely mapped reads.
This workflow takes as input a list of paired-end fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously. The counts are reprocess to be similar to HTSeq-count output. FPKM are computed with cufflinks. Coverage (per million mapped reads) are computed with bedtools on uniquely mapped reads (with R2 orientation inverted).
Alignment, assembly and annotation of RNQSEQ reads using TOPHAT (without filtering out host reads).
DownloadThis workflow has been created as part of Demonstrator 6 of the project EOSC-Life (within WP3) and is focused on reusing publicly available RNAi screens to gain insights into the nucleolus biology. The workflow downloads images from the Image Data Resource (IDR), performs object segmentation (of nuclei and nucleoli) and feature extraction of the images and objects identified.
This portion of the workflow produces sets of feature Counts ready for analysis by limma/etc.
Type: Galaxy
Creators: Iacopo Cristoferi, Helena Rasche, Clinical Bioinformatics Unit, Pathology Department, Eramus Medical Center
Submitter: Helena Rasche
RNA-RNA interactome analysis using ChiRA tools suite. The aligner used is CLAN.
RNA-RNA interactome analysis using ChiRA tools suite. The aligner used is BWA-MEM.
Performs scaffolding using Bionano Data. Part of VGP assembly pipeline.
Performs Long Read assembly using PacBio data and Hifiasm. Part of VGP assembly pipeline. This workflow generate a phased assembly.
Performs Long Read assembly using PacBio data and Hifiasm. Part of VGP assembly pipeline. This workflow generate a phased assembly.
Performs scaffolding using HiC Data. Part of VGP assembly pipeline. The scaffolding can be performed on long read assembly contigs or on scaffolds (e.g.: Bionano scaffolds).
This is part of a series of workflows to annotate a genome, tagged with TSI-annotation.
These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.
The workflows can be run in this order:
- Repeat masking
- RNAseq QC and read trimming
- Find transcripts
- Combine transcripts
- Extract transcripts
- Convert formats
- Fgenesh annotation
About this workflow:
- Run this workflow per tissue.
- Inputs: masked_genome.fasta and the trimmed RNAseq reads ...
