Alert.png The wiki is deprecated and due to be decommissioned by the end of September 2022.
The content is being migrated to other supports, new updates will be ignored and lost.
If needed you can get in touch with EGI SDIS team using operations @


From EGIWiki
Jump to navigation Jump to search
Overview For users For resource providers Infrastructure status Site-specific configuration Architecture

Federated Cloud Communities menu: Home Production use cases Under development use cases Closed use cases High level tools use cases

General Information

  • Status: Production
  • Start Date: 01/03/2014
  • End Date: In production from 03/11/2014
  • Cloud sites: GoeGrid, IFCA
  • Virtual Organisation:
  • contact: Diego Scardaci /
  • External contact: Konrad Foerstner /

Short Description

READemption is a pipeline for the computational evaluation of RNA-Seq data. It was originally developed to process dRNA-Seq reads (as introduced by Sharma et al., Nature, 2010 (Pubmed)) originating from bacterial samples. Meanwhile is has been extended to process data generated in different experimental setups and from all domains of life. The functions which are accessible via a command-line interface cover read processing and aligning, coverage calculation, gene expression quantification, differential gene expression analysis as well as visualization. In order to set up and perform analyses quickly READemption follows the principal of convention over configuration: Once the input files are copied/linked into defined folders no further parameters have to be given. Still, READemption’s behavior can be adapted to specific needs of the user by parameters.

The READemption community already have a computational infrastructure which is usually fine but they have some situations when they got a lot of data and peaks of demand. Then, sometimes they used Amazon to manage these peaks. They created some instances, uploaded the data, run the application, got the result and kill the VM, usually for 1 or 2 days, sometimes longer. This working model is very expensive for the community and they can use it only for really important projects.

Aim of this use case is using the EGI Federated Cloud to manage the peaks of demand instead of Amazon.

Use Case

Run READemption on the EGI Federated Cloud


  • 2/3 VMs with linux operating system (Ubuntu 14 is the favourite)
  • more than 20 cores
  • more than 70 GB of memory
  • around 1 TB of storage (block storage)

Additional Files