MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure.

TitleMAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure.
Publication TypeJournal Article
Year of Publication2014
AuthorsKim J, Levy E, Ferbrache A, Stepanowsky P, Farcas C, Wang S, Brunner S, Bath T, Wu Y, Ohno-Machado L
JournalBioinformatics
Volume30
Issue19
Pagination2826-7
Date Published2014 Oct
ISSN1367-4811
KeywordsComputational Biology, Computer Graphics, Internet, MicroRNAs, Programming Languages, Sequence Analysis, RNA, Software
Abstract

SUMMARY: MAGI is a web service for fast MicroRNA-Seq data analysis in a graphics processing unit (GPU) infrastructure. Using just a browser, users have access to results as web reports in just a few hours->600% end-to-end performance improvement over state of the art. MAGI's salient features are (i) transfer of large input files in native FASTA with Qualities (FASTQ) format through drag-and-drop operations, (ii) rapid prediction of microRNA target genes leveraging parallel computing with GPU devices, (iii) all-in-one analytics with novel feature extraction, statistical test for differential expression and diagnostic plot generation for quality control and (iv) interactive visualization and exploration of results in web reports that are readily available for publication.

AVAILABILITY AND IMPLEMENTATION: MAGI relies on the Node.js JavaScript framework, along with NVIDIA CUDA C, PHP: Hypertext Preprocessor (PHP), Perl and R. It is freely available at http://magi.ucsd.edu.

DOI10.1093/bioinformatics/btu377
PubMed URLhttp://www.ncbi.nlm.nih.gov/pubmed/24907367?dopt=Abstract
Alternate JournalBioinformatics
PubMed ID24907367
PubMed Central IDPMC4173015
Grant ListT15 LM011271 / LM / NLM NIH HHS / United States
U54HL108460 / HL / NHLBI NIH HHS / United States
Track(s): 
Biomedical Informatics