Workflows

What is a Workflow?
840 Workflows visible to you, out of a total of 916
Allele-specific expression-network clustering analysis for Huntington's Disease
No description specified

Type: Common Workflow Language

Creators: None

Submitter: Aishwarya Iyer

nf-core/pixelator

GitHub Actions CI Status GitHub Actions Linting StatusAWS CI[![Cite ...

Type: Nextflow

Creator: Pixelgen Technologies AB

Submitter: WorkflowHub Bot

mettannotator
Stable

Nextflow run with docker run with singularity

mettannotator

Type: Nextflow

Creators: Tatiana Gurbich, Martin Beracochea

Submitter: Martin Beracochea

A workflow to extract individual trees from 3D point cloud data obtained by airborne laser scanning

Point-based Individual Tree Delineation from 3D LiDAR Point Cloud Data.

This module implements a lightweight and easy-to-use Point-based method for individual tree delineation from 3D point cloud data using pure C/C++.

The source code files are included in folder [TreeSeparation], which consists of a project generated from Visual Studio 2015. The CLASS for tree separation is named "FoxTree" and can be found in the respect FoxTree.h and FoxTree.cpp files.

Inupt

The ...

Type: Unrecognized workflow type

Creators: None

Submitter: Jinhu Wang

nf-core/rangeland

GitHub Actions CI Status GitHub Actions Linting StatusAWS CI[![Cite ...

Type: Nextflow

Creators: None

Submitter: WorkflowHub Bot

Use case 9: Explore regulatory information associated with a regulatory element

The workflow starts with selecting EH38E2924876 as the search term. Genomic position of provided unique regulatory element identifier was retrieved from CFDE Linked Data Hub[1]. A list of variants in the region of the regulatory element was retrieved from CFDE Linked Data Hub[1]. Variant/variant set associated allele specific epigenomic signatures were retrieved from CFDE LDH[5] based on Roadmap and ENTEx data[6], [4]. GTEx eQTL and sQTL evidence for the given variant(s) were retrieved from CFDE ...

Type: Playbook Workflow Builder Workflow

Creator: Playbook Partnership NIH CFDE

Submitter: Daniel Clarke

DOI: 10.48546/workflowhub.workflow.1249.3

Use Case 3: Compounds to Reverse Disease Signatures

A file containing GEO Aging Signatures was first uploaded. The file containing GEO Aging Signatures was loaded as a gene signature. A file containing GTEx Aging Signatures was first uploaded. The file containing GTEx Aging Signatures was loaded as a gene signature. Significant genes were extracted from the GEO Aging Signatures. Significant genes were extracted from the GTEx Aging Signatures. Reversers and mimickers from over 1 million signatures were identified using SigCom LINCS[1]. Resolved ...

Type: Playbook Workflow Builder Workflow

Creator: Playbook Partnership NIH CFDE

Submitter: Daniel Clarke

DOI: 10.48546/workflowhub.workflow.1248.2

Use Case 13: Novel Cell Surface Targets for Individual Cancer Patients Analyzed with Common Fund Datasets

A file was first uploaded. The file was parsed as a gene count matrix. Significantly over-expressed genes when compared to tissue expression in GTEx[1] were identified. RNA-seq-like LINCS L1000 Signatures[3] which mimick or reverse the the expression of IMP3 were visualized. Drugs which down-regulate the expression of IMP3 were identified from the RNA-seq-like LINCS L1000 Chemical Perturbagens[3]. Genes which down-regulate the expression of IMP3 were identified from the RNA-seq-like LINCS L1000 ...

Type: Playbook Workflow Builder Workflow

Creator: Playbook Partnership NIH CFDE

Submitter: Daniel Clarke

DOI: 10.48546/workflowhub.workflow.1246.2

Use Case 11: Related Proteins/Metabolites across DCCs

The workflow starts with selecting RPE as the search term. For the given gene ID (SYMBOL), StringDB PPI was extracted using their API[1]. For the Given StringDB PPI, the list of nodes (Gene Set) is generated. For the Given StringDB PPI, the list of nodes (GeneSet) is generated. Reversers and mimickers from over 1 million signatures were identified using SigCom LINCS[2]. The gene set was submitted to Enrichr[4]. The gene set was then searched in the Metabolomics Workbench[5] to identify relevant ...

Type: Playbook Workflow Builder Workflow

Creator: Playbook Partnership NIH CFDE

Submitter: Daniel Clarke

DOI: 10.48546/workflowhub.workflow.1245.2

Use Case 10: Guilt by Association

The workflow starts with a gene set created from Example gene set. CTD is applied which diffuses through all nodes in STRING[1] to identify nodes that are "guilty by association" and highly connected to the initial gene set of interest[2][3]. A list of Highly Connected Genes was obtained from the CTD output. A list of Guilty By Association Genes was obtained from the CTD output.

  1. Szklarczyk, D. et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic ...

Type: Playbook Workflow Builder Workflow

Creator: Playbook Partnership NIH CFDE

Submitter: Daniel Clarke

DOI: 10.48546/workflowhub.workflow.1244.2

Powered by
 (v.1.16.0)
About WorkflowHub | Acknowledgements | Credits | Terms & Conditions | Privacy Policy | Cite us | Contact us
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH