Workflows

What is a Workflow?
1484 Workflows visible to you, out of a total of 1582

An example how ISCC codes can be used to verify image analysis steps

Associated Tutorial

This workflows is part of the tutorial Content Tracking and Verification in Galaxy Workflows with ISCC-SUM, available in the GTN

Features

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Type: Galaxy

Creators: None

Submitter: GTN Bot

This workflow is executing a BiaPy workflow using a YAML file where the model selection is predefined.

Associated Tutorial

This workflows is part of the tutorial Execute a BiaPy workflow in Galaxy, available in the GTN

Features

...

Type: Galaxy

Creators: None

Submitter: GTN Bot

No description specified
No description specified

Type: Galaxy

Creators: None

Submitter: Thomas N

No description specified

Type: Galaxy

Creators: None

Submitter: Thomas N

No description specified

Type: Galaxy

Creators: None

Submitter: Thomas N

Stable
No description specified

Type: Galaxy

Creators: None

Submitter: Thomas N

Stable

The workflow takes a trimmed long reads collection, and Forward/Reverse HiC reads to run Hifiasm in HiC phasing mode. It produces both Pri/Alt and Hap1/Hap2 assemblies, and runs all the QC analysis (gfastats, BUSCO, and Merqury). The default Hifiasm purge level is aggressive (l3).

Type: Galaxy

Creators: Diego De Panis, ERGA

Submitter: Diego De Panis

DOI: 10.48546/workflowhub.workflow.605.1

Stable

The workflow takes a (trimmed) Long reads collection, runs Meryl to create a K-mer database, Genomescope2 to estimate genome properties and Smudgeplot to estimate ploidy (optional). The main results are K-mer database and genome profiling plots, tables, and values useful for downstream analysis. Default K-mer length and ploidy for Genomescope are 31 and 2, respectively.

Type: Galaxy

Creators: Diego De Panis, ERGA

Submitter: Diego De Panis

DOI: 10.48546/workflowhub.workflow.603.1

Stable

Hep_Ploidy_protocol

This is the ploidy identification workflow from the article "Stereo-cell Deciphers the Spatial and Functional Heterogeneity of Polyploid Hepatocytes". The method employs deep learning techniques: Cellpose & StarDist to accurately identify DAPI fluorescence-stained images and brightfield images, respectively. It acquires detailed information on the morphological characteristics and spatial localization of nuclei and cells, which serves as the core process for hepatocyte ...

Type: Unrecognized workflow type

Creators: Jiahui Luo, Shijie Hao, Yongqing Yang, Zhi Huang

Submitter: Jiahui Luo

DOI: 10.48546/workflowhub.workflow.2079.3

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