Dataset Information


Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

ABSTRACT: Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost.


PROVIDER: S-EPMC4350034 | BioStudies | 2015-01-01T00:00:00Z

REPOSITORIES: biostudies

Similar Datasets

2014-01-01 | S-EPMC4172764 | BioStudies
1000-01-01 | S-EPMC3098063 | BioStudies
2011-01-01 | S-EPMC3150038 | BioStudies
2012-01-01 | S-EPMC3521398 | BioStudies
2018-01-01 | S-EPMC6091888 | BioStudies
2020-01-01 | S-EPMC7319573 | BioStudies
2017-01-01 | S-EPMC5467033 | BioStudies
2016-01-01 | S-EPMC5333212 | BioStudies
2015-01-01 | S-EPMC4482534 | BioStudies
2017-01-01 | S-EPMC5537389 | BioStudies