Workflows

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556 Workflows visible to you, out of a total of 599
Java COMPSs wordcount example (laptop run, files used as inputs)
Stable

Name: Java Wordcount Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Wordcount application. There are two versions of Wordcount, depending on how the input data is given.

Version 1

''Single input file'', where all the text is given in the same file and the chunks are calculated with a BLOCK_SIZE parameter.

Version 2

''Multiple input files'', where the text fragments are already in different files under ...

Type: COMPSs

Creators: Jorge Ejarque, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)

Submitter: Raül Sirvent

DOI: 10.48546/workflowhub.workflow.684.1

gcms-metams/main

This workflow is composed with the XCMS tool R package (Smith, C.A. 2006) able to extract and the metaMS R package (Wehrens, R 2014) for the field of untargeted metabolomics.

https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/gcms/tutorial.html

Type: Galaxy

Creator: workflow4metabolomics

Submitter: WorkflowHub Bot

ANNOTATO - ERGA Genome Annotation Workflow in Nextflow
Stable

ANNOTATO - Annotation workflow To Annotate Them Oll

Type: Nextflow

Creator: Phuong Doan

Submitters: Tom Brown, Phuong Doan

DOI: 10.48546/workflowhub.workflow.654.2

PyCOMPSs Increment example, ran at Marenostrum IV supercomputer, example of INOUT file and compss_open usage
Stable

Name: Increment Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Increment is an application that takes three different values and increases them a number of given times.

The purpose of this application is to show parallelism between the different increments.

Execution instructions

Usage:

runcompss --lang=python src/increment.py N initValue1 initValue2 initValue3

where:

  • N: Number of times to increase ...

Type: COMPSs

Creators: Javier Conejero, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)

Submitter: Raül Sirvent

DOI: 10.48546/workflowhub.workflow.678.1

gromacs-mmgbsa/main

MMGBSA simulation and calculation

Type: Galaxy

Creators: Simon Bray, Simon Bray

Submitter: WorkflowHub Bot

kmer-profiling-hifi-VGP1/main

VGP Workflow #1

This workflow produces a Meryl database and Genomescope outputs that will be used to determine parameters for following workflows, and assess the quality of genome assemblies. Specifically, it provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality.

Inputs

  • A collection of Hifi long reads in FASTQ format
  • k-mer length
  • Ploidy

Outputs

  • Meryl Database of kmer counts

...

Type: Galaxy

Creator: VGP, Galaxy

Submitter: WorkflowHub Bot

kmer-profiling-hifi-trio-VGP2/main

Create Meryl Database used for the estimation of assembly parameters and quality control with Merqury. Part of the VGP pipeline.

Type: Galaxy

Creator: VGP, Galaxy

Submitter: WorkflowHub Bot

lcms-preprocessing/main

This workflow is composed with the XCMS tool R package (Smith, C.A. 2006) able to extract, filter, align and fill gapand the possibility to annotate isotopes, adducts and fragments using the CAMERA R package (Kuhl, C 2012).

https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html

Type: Galaxy

Creator: workflow4metabolomics

Submitter: WorkflowHub Bot

Somatic-Variant-Discovery-from-WES-Data-Using-Control-FREEC
Stable

This workflow is created as part of a tutorial listed on GTN. The workflow shows the steps in human copy number variance detection using the Contrl_FREEC tool.

Type: Galaxy

Creators: khaled Jumah, Katarzyna Kamieniecka, Wolfgang Maier, Krzysztof Poterlowicz, poterlowicz-lab

Submitter: Khaled Jum'ah

DOI: 10.48546/workflowhub.workflow.676.1

Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data
Stable

Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data

In recent years, convolutional neural network (CNN)-based methods have shown remarkable performance in the denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures have been the main focus of existing studies. Recently, however, an alternative and highly competitive deep learning architecture, ...

Type: Python

Creator: Zafran Hussain Shah

Submitter: Zafran Hussain Shah

DOI: 10.48546/workflowhub.workflow.675.1

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