Cloud CPFP: A Shotgun Proteomics Data Analysis Pipeline Using Cloud and High Performance Computing

J Proteome Res. 2012 Dec 7;11(12):6282-90. doi: 10.1021/pr300694b. Epub 2012 Oct 29.

Abstract

We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Line
  • Computational Biology / economics
  • Computational Biology / methods*
  • Databases, Protein
  • Electronic Data Processing / methods
  • Humans
  • Internet
  • Proteomics / economics
  • Proteomics / methods*
  • Reproducibility of Results
  • Search Engine
  • Software*
  • Time Factors