Workflows

What is a Workflow?
Created At
Go
Updated At
Go
39 Workflows visible to you, out of a total of 80
Tests: All failing

This workflow take as input a collection of paired fastq. It will remove bad quality and adapters with cutadapt. Map with Bowtie2 end-to-end. Will remove reads on MT and unconcordant pairs and pairs with mapping quality below 30 and PCR duplicates. Will compute the pile-up on 5' +- 100bp. Will call peaks and count the number of reads falling in the 1kb region centered on the summit. Will plot the number of reads for each fragment length.

Type: Galaxy

Creator: Lucille Delisle

Submitter: Finn Bacall

K-means clustering is a method of cluster analysis that aims to partition ''n'' points into ''k'' clusters in which each point belongs to the cluster with the nearest mean. It follows an iterative refinement strategy to find the centers of natural clusters in the data.

Type: PyCOMPSs

Creators: None

Submitter: Raül Sirvent

Hypermatrix size 2x2 blocks, block size 2x2 elements

Type: PyCOMPSs

Creator: Raül Sirvent

Submitter: Raül Sirvent

Hypermatrix size 2x2 blocks, block size 2x2 elements

Type: PyCOMPSs

Creator: Raül Sirvent

Submitter: Raül Sirvent

Hypermatrix size 2x2 blocks, block size 2x2 elements

Type: PyCOMPSs

Creator: Raül Sirvent

Submitter: Raül Sirvent

Hypermatrix size 2x2 blocks, block size 2x2 elements

Type: PyCOMPSs

Creator: Raül Sirvent

Submitter: Raül Sirvent

Hypermatrix size 2x2 blocks, block size 2x2 elements

Type: PyCOMPSs

Creator: Raül Sirvent

Submitter: Raül Sirvent

Powered by
(v.1.13.0-master)
Copyright © 2008 - 2022 The University of Manchester and HITS gGmbH