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738 Workflows visible to you, out of a total of 793
Assembly-Hifi-HiC-phasing-VGP4/main

Contiging Solo w/HiC:

Generate phased assembly based on PacBio Hifi Reads using HiC data from the same individual for phasing.

Inputs

  1. Hifi long reads [fastq]
  2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]
  3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]
  4. K-mer database [meryldb]
  5. Genome profile summary generated by Genomescope [txt]
  6. Name of first assembly
  7. Name of second assembly ...

Type: Galaxy

Creators: Delphine Lariviere, Galaxy, VGP

Submitter: WorkflowHub Bot

Autosubmit mHM test domains
Work-in-progress

Autosubmit mHM test domains

Type: Autosubmit

Creator: Bruno P. Kinoshita

Submitter: Bruno P. Kinoshita

ERGA HiC Hap1Hap2 Scaffolding+QC YaHS v2309 (WF4)
Stable

The workflow takes trimmed HiC forward and reverse reads, and Hap1/Hap2 assemblies to produce Hap1 and Hap2 scaffolded assemblies using YaHS. It also runs all the QC analyses (gfastats, BUSCO, Merqury and Pretext).

Type: Galaxy

Creators: Diego De Panis, ERGA

Submitter: Diego De Panis

DOI: 10.48546/workflowhub.workflow.608.1

Java COMPSs LU Factorization for Sparse Matrices
Stable

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

Description

The Sparse LU application computes an LU matrix factorization on a sparse blocked matrix. The matrix size (number of blocks) and the block size are parameters of the application.

As the algorithm progresses, the area of the matrix that is accessed is smaller; concretely, at each iteration, the 0th row and column of the current matrix are discarded. ...

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.515.1

Cancer variant annotation (hg38 VEP-based) with MAF export
Stable

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 ...

Type: Galaxy

Creator: Wolfgang Maier

Submitter: Wolfgang Maier

DOI: 10.48546/workflowhub.workflow.629.1

Variant calling from matched tumor/normal sample pair (hg38 version)
Stable

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 ...

Type: Galaxy

Creator: Wolfgang Maier

Submitter: Wolfgang Maier

DOI: 10.48546/workflowhub.workflow.628.1

PyCOMPSs Matrix Multiplication with Objects (inputs generated by the code)
Stable

Name: Matrix multiplication with Objects Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.

If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the ...

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.627.1

MMV_Im2Im

MMV Im2Im Transformation

Build Status

A generic python package for deep learning based image-to-image transformation in biomedical applications

The main branch will be further developed in order to be able to use the latest state of the art techniques and methods in the future. To reproduce the results of our manuscript, we refer to the branch ...

Type: Python

Creator: Justin Sonneck

Submitter: Justin Sonneck

DOI: 10.48546/workflowhub.workflow.626.1

Java COMPSs Matrix Multiplication, out-of-core, using files

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

Description

Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.

If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the elements of the ...

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.484.1

PyCOMPSs Matrix Multiplication, out-of-core, using files

Name: Matrix multiplication with Files Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.

If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the elements ...

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.485.1

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