title: Compression of Large genomic datasets using COMRAD on Parallel Computing Platform.
abstract: The big data storage is a challenge in a post genome era. Hence, there is a need for high performance computing solutions for managing large genomic data. Therefore, it is of interest to describe a parallel-computing approach using message-passing library for distributing the different compression stages in clusters. The genomic compression helps to reduce the on disk"foot print" of large data volumes of sequences. This supports the computational infrastructure for a more efficient archiving. The approach was shown to find utility in 21 Eukaryotic genomes using stratified sampling in this report. The method achieves an average of 6-fold disk space reduction with three times better compression time than COMRAD.
  
  
  BACKGROUND
  The source codes are written in C using message passing libraries and are available at https:// sourceforge.net/ projects/ comradmpi/files / COMRADMPI/.
authors.affiliation: Department of Computational Biology and Bioinformatics, University of Kerala, Thiruvananthapuram.
authors.forename: Christopher Leela
authors.initials: CL
authors.lastname: Biji
authors.affiliation: School of Computer Science, Mahathma Gandhi University, Kottayam.
authors.forename: Manu K
authors.initials: MK
authors.lastname: Madhu
authors.affiliation: Infosys Technologies, Trivandrum.
authors.forename: Vineetha
authors.initials: V
authors.lastname: Vishnu
authors.affiliation: Department of Future Studies, University of Kerala, Thiruvananthapuram.
authors.forename: Satheesh Kumar
authors.initials: SK
authors.lastname: K
authors.affiliation: School of Computer Science, Mahathma Gandhi University, Kottayam.
authors.lastname: Vijayakumar
authors.affiliation: Department of Computational Biology and Bioinformatics, University of Kerala, Thiruvananthapuram.
authors.forename: Achuthsankar S
authors.initials: AS
authors.lastname: Nair
keywords: Big data storage; Genome Analysis; Genome compression; Parallel Computing; Sequence analysis