This dataset contains small files that are used for the https://rna.usegalaxy.eu/tours/rnateam.viennarna

Restart files for CLM-FATES version 2.0.1 for CLM-FATES EMERALD version 2.0.1.

CTSM_FATES-EMERALD_on_inputdata_version2.0.0_ALP1.tar_(restart_info):
- ALP1_refcase.datm.r.2300-01-01-00000.nc
- ALP1_refcase.datm.rs1.2300-01-01-00000.bin
- ALP1_refcase.cpl.r.2300-01-01-00000.nc
- ALP1_refcase.clm2.r.2300-01-01-00000.nc

This dataset is being used in the Galaxy Training tutorial on CLM-FATES.

This work has been done in in collaboration with Galaxy Europe and EOSC-Life:
- Within the 1st EOSC-Life Training Open Call, two out of four proposals have been awarded to the European Galaxy team to develop climate science e-learning material and mentoring and training opportunities for our communities.

CLM-FATES documentation can be found here.

Data from https://trace.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?exp=SRX105188&cmd=search&m=downloads&s=seq and ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/002/985/GCA_000002985.3_WBcel235

For Galaxy Training https://rna.usegalaxy.eu/workflows/run?id=a108b575b16e6cb9

Additional file 5: Supplementary Figure S1. Galaxy web interface of LotuS2. Raw reads can be uploaded into the LotuS2 via the Galaxy web interface and analysed (accessible on https://usegalaxy.eu/ ).

Datasets for Transformer-based tool recommeder in Galaxy:

1. Tool popularity - Contains last one year usage of all Galaxy tools per month (Extracted from Galaxy Europe using query https://github.com/galaxyproject/gxadmin/blob/main/docs/README.query.md#query-tool-popularity)

2. Workflow connections - Contains workflows as tabular files as pairs of tools - IN and OUT (Extracted from Galaxy Europe using query https://github.com/galaxyproject/gxadmin/blob/main/docs/README.query.md#query-workflow-connections)

This repository contains datasets required for the online training "Data analysis and interpretation for clinical genomics" available at https://sigu-training.github.io/clinical_genomics/.

Tools used in the training are available at the European Galaxy instance running at https://usegalaxy.eu, which also includes a copy of this repository in the Shared Data Libraries. BAM files in this dataset are based on the hg38 reference genome.

This is part of a 4 dataset submission. Refer to this dataset for details.

The data here is a subset of the data published in 10.5281/zenodo.3732359 to be used in GTN 'Upload data to ENA' tutorial.

Human traces have been removed following https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/human-reads-removal/tutorial.html

We produced consensus sequences (*.fasta) for the Illumina PE data following SARS-CoV-2-PE-Illumina-WGS-variant-calling (https://workflowhub.eu/workflows/113?version=4), SARS-CoV-2-variation-reporting (https://workflowhub.eu/workflows/109?version=5) and COVID-19-consensus-construction (https://workflowhub.eu/workflows/138?version=4) workflows.

This training dataset is from an imaginary Staphylococcus aureus bacterium with a miniature genome. There is a reference genome in various formats as well as some fastq reads of a closely related but also imaginary mutant strain.

It is a useful dataset for demonstrating:

• de novo genome assembly
• read mapping and variant calling
• genome annotation

The files included are:

• wildtype.fna: the reference genome sequence of the wildtype strain in fasta format (a header line, then the nucleotide sequence of the genome.)
• wildtype.gff: the reference genome sequence of the wildtype strain in general feature format (a list of features - one feature per line, then the nucleotide sequence of the genome.)
• wildtype.gbk: the reference genome sequence in genbank format.
• mutant_R1.fastq and mutant_R2.fastq: Fastq sequence reads of a closely related mutant strain.
  • The reads are paired-end.
  • Each read is 150 bases long.
  • The number of bases sequenced is equivalent to 19x the genome sequence of the wildtype strain. (Read coverage 19x - rather low!).

ERA5-Land monthly averaged data January 2019 Dataset has been retrieved on the Copernicus Climate data Store (https://cds.climate.copernicus.eu/#!/home) and is meant to be used for teaching purposes only. This dataset is used in the Galaxy training on "Visualize Climate data with Panoply in Galaxy". See https://training.galaxyproject.org/ (topic: climate) for more information. Product type: Monthly averaged reanalysis Variable: 10m u-component of wind, 10m v-component of wind, 2m temperature, Leaf area index, high vegetation, Leaf area index, low vegetation, Snow cover, Snow depth Year: 2019 Month: January Time: 00:00 Format: NetCDF (experimental)

In years 2018-2019, we organized on behalf of the Italian Society of Human Genetics (SIGU) an itinerant Galaxy-based “hands-on-computer” training activity entitled “Data analysis and interpretation for clinical genomics”. This one-day course was offered to participants including clinical doctors, biologists, laboratory technicians and bioinformaticians. Topics covered by the course were NGS data quality check, detection of variants, copy number alterations and runs of homozygosity, annotation and filtering and clinical interpretation of sequencing results.

To meet the constant need for training on basic NGS analysis and interpretation of sequencing data in the clinical setting, we designed an on-line Galaxy-based training resource dedicated to this topic, articulated in presentations and practical assignments by which students will learn how to approach NGS data processing at the level of FASTQ, BAM and VCF files and clinically-oriented examination of variants emerging from sequencing experiments such as whole exomes.

This repository contains datasets required for the online training "Data analysis and interpretation for clinical genomics" available at https://sigu-training.github.io/clinical_genomics/.

Tools used in the training are available at the European Galaxy instance running at https://usegalaxy.eu, which also includes a copy of this repository in the Shared Data Libraries. Files named Fam_*.bam are based on hg38 reference genome; all the other files refer to hg19.

This is part of a 4 dataset submission.

Credit report of Galaxy Europe B.v. contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Dataset has been retrieved on the Copernicus Climate data Store (https://cds.climate.copernicus.eu/#!/home) and is meant to be used for teaching purposes only. Data retrieved were split per year and concatenated to create two separate files. Then these two files were converted from GRIB format to netcdf using xarray (http://xarray.pydata.org/en/stable/). This dataset is used in the Galaxy training on "Visualize Climate data with Panoply in Galaxy".

See https://training.galaxyproject.org/ (topic: climate) for more information.

The python code below show how it has been retrieved on CDS:

import cdsapi

c = cdsapi.Client()

c.retrieve(
'ecv-for-climate-change',
{
'variable': [
'precipitation', 'sea_ice_cover', 'surface_air_temperature',
],
'product_type': 'monthly_mean',
'time_aggregation': '1_month',
'year': [
'1979', '2018',
],
'month': [
'01', '02', '03',
'04', '05', '06',
'07', '08', '09',
'10', '11', '12',
],
'origin': 'era5',
'format': 'zip',
},
'download.zip')

Real galaxy dataset extracted from the HST COSMOS survey for use with GalSim.

The statistic shows the market share of smartphones in use in Europe, by device, from the second quarter of 2015 to the second quarter of 2018. The Apple iPhone X model had a market share of 1.9 percent in the second quarter of 2018.

The statistic shows the market share of tablets in use in Europe, by device, from the second quarter of 2015 to the second quarter of 2018. The Apple iPad Air model had a market share of 8.14 percent in the second quarter of 2018.

Downsampled datasets for the small genome assembly in Galaxy training. These include 3 files : forward and reverse reads from Illumina sequencing , and Long read file from Oxford Nanopore sequencing.

This dataset provides the inputs needed for the Galaxy Pathway Analysis workflow training tutorial (https://galaxy-synbiocad.org).

This workflow asseses the performance of predicted pathways by computing 4 criteria (target product flux, thermodynamic feasibility, pathway length, and enzyme availability). A score inform the user about the best candidate pathways to produce a compound of interest. The generated output is a collection of scored and ranked heterologous pathways.

The content of the dataset is as follows:

• A set of pathways provided in the SBML format (Systems Biology Markup Language) to be ranked, modeling heterologous pathways such as those outputted by the RetroSynthesis workflow (https://galaxy-synbiocad.org).

• The GEM (Genome-scale metabolic models) which is a formalized representation of the metabolism of the host organism (the model is E. coli iML1515), provided in the SBML format.

The NCBI BLAST suite has become ubiquitous in modern molecular biology and is used for small tasks such as checking capillary sequencing results of single PCR products, genome annotation or even larger scale pan-genome analyses. For early adopters of the Galaxy web-based biomedical data analysis platform, integrating BLAST into Galaxy was a natural step for sequence comparison workflows. Here we provide the command line NCBI BLAST+ tool suite wrapped for use within Galaxy.
The integration of the BLAST+ tool suite into Galaxy has the goal of making common BLAST tasks easy and advanced tasks possible. This project is an informal international collaborative effort, it is deployed and used on Galaxy servers worldwide.

Phylogenetic information inferred from the study of homologous genes helps us to understand the evolution of genes and gene families, including the identification of ancestral gene duplication events as well as regions under positive or purifying selection within lineages. Gene family and orthogroup characterisation enables the identification of syntenic blocks, which can then be visualised with various tools. Unfortunately, currently available tools display only an overview of syntenic regions as a whole, limited to the gene level, and none provide further details about structural changes within genes, such as the conservation of ancestral exon boundaries amongst multiple genomes. We present Aequatus, a standalone web-based tool that provides an in-depth view of gene structure across gene families, with various options to render and filter visualisations. It relies on pre-calculated alignment and gene feature information typically held in, but not limited to, the Ensembl Compara and Core databases. We also offer Aequatus.js, a reusable JavaScript module that fulfils the visualisation aspects of Aequatus, available within the Galaxy web platform as a visualisation plugin, which can be used to visualise gene trees generated by the GeneSeqToFamily workflow. Aequatus is an open-source tool freely available to download under the MIT license at https://github.com/TGAC/Aequatus A demo server is available at http://aequatus.earlham.ac.uk/ A publicly available instance of the GeneSeqToFamily workflow to generate gene tree information and visualise it using Aequatus is available on the Galaxy EU server at https://usegalaxy.eu

This database includes the environment catalogue presented in Fossati et al. 2016