mRNA-Seq BY-COVID Pipeline: Counts Version 1
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Run on GalaxyThis portion of the workflow produces sets of feature Counts ready for analysis by limma/etc.
Inputs
| ID | Name | Description | Type |
|---|---|---|---|
| UCSC Genome | #main/UCSC Genome | Export of UCSC Genome, just the genes. |
|
| mRNA-Seq Reads | #main/mRNA-Seq Reads | Input list of fastqsanger format sequencing data |
|
Steps
| ID | Name | Description |
|---|---|---|
| 2 | FastQC | toolshed.g2.bx.psu.edu/repos/devteam/fastqc/fastqc/0.74+galaxy0 |
| 3 | Cutadapt | toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0 |
| 4 | FastQC | toolshed.g2.bx.psu.edu/repos/devteam/fastqc/fastqc/0.74+galaxy0 |
| 5 | HISAT2 | toolshed.g2.bx.psu.edu/repos/iuc/hisat2/hisat2/2.2.1+galaxy1 |
| 6 | featureCounts | toolshed.g2.bx.psu.edu/repos/iuc/featurecounts/featurecounts/2.0.3+galaxy1 |
| 7 | Read Distribution | toolshed.g2.bx.psu.edu/repos/nilesh/rseqc/rseqc_read_distribution/5.0.1+galaxy2 |
| 8 | Gene Body Coverage (BAM) | toolshed.g2.bx.psu.edu/repos/nilesh/rseqc/rseqc_geneBody_coverage/5.0.1+galaxy2 |
| 9 | Multi QC raw reads | toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1 |
Outputs
| ID | Name | Description | Type |
|---|---|---|---|
| html_report | #main/html_report | n/a |
|
| output_feature_lengths | #main/output_feature_lengths | n/a |
|
| output_short | #main/output_short | n/a |
|
Version History
Version 1 (earliest) Created 19th Dec 2023 at 10:10 by Helena Rasche
Initial commit
Frozen
Version-17f98d5d
Creators and SubmitterCreators
Additional credit
Clinical Bioinformatics Unit, Pathology Department, Eramus Medical Center
Submitter
Views: 2589 Downloads: 424 Runs: 0
Created: 19th Dec 2023 at 10:09
AttributionsNone
Related items
https://orcid.org/0000-0001-9760-8992Failure is not an option.
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ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. These resources include databases, software tools, training materials, cloud storage and supercomputers.
The goal of ELIXIR is to coordinate these resources so that they form a single infrastructure. This infrastructure makes it easier for scientists to find and share data, exchange expertise, and agree on best practices. Ultimately, it will help them gain new insights into how living ...
Teams: ELIXIR Training, FAIR Computational Workflows, EuroScienceGateway, BY-COVID (general), ELIXIR Tools platform, ELIXIR Metabolomics
Web page: https://elixir-europe.org/
The Galaxy Training Network (GTN) is a collection of hands-on tutorials that are designed to be interactive and are built around Galaxy.
These tutorials can be used for learning and teaching how to use Galaxy for general data analysis, as well as a wide array of hands-on tutorials covering specific domains such as assembly, RNA-Seq analysis, deep learning, climate analysis, and more!
Team for general BY-COVID contributions
Space: ELIXIR
Public web page: Not specified
canonical record: https://zenodo.org/records/10405036
Source data (GSE182152) was analysed with WFHub:688 to generate these datasets
Creators: Helena Rasche, Iacopo Cristoferi, Marek Ostaszewski, Andrew Stubbs
Submitter: Helena Rasche
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