READSCAN: A fast and scalable pathogen discovery program with accurate genome relative abundance estimation

Handle URI:
http://hdl.handle.net/10754/325436
Title:
READSCAN: A fast and scalable pathogen discovery program with accurate genome relative abundance estimation
Authors:
Naeem, Raeece ( 0000-0003-1734-1007 ) ; Rashid, Mamoon ( 0000-0003-4851-4994 ) ; Pain, Arnab ( 0000-0002-1755-2819 )
Abstract:
Summary: READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). Availability: http://cbrc.kaust.edu.sa/readscan Contact: or raeece.naeem@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. 2012 The Author(s).
KAUST Department:
Computational Bioscience Research Center (CBRC); Pathogen Genomics Laboratory
Citation:
Naeem R, Rashid M, Pain A (2012) READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimation. Bioinformatics 29: 391-392. doi:10.1093/bioinformatics/bts684.
Publisher:
Oxford University Press
Journal:
Bioinformatics
Issue Date:
28-Nov-2012
DOI:
10.1093/bioinformatics/bts684
PubMed ID:
23193222
PubMed Central ID:
PMC3562070
Type:
Article
ISSN:
13674803
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorNaeem, Raeeceen
dc.contributor.authorRashid, Mamoonen
dc.contributor.authorPain, Arnaben
dc.date.accessioned2014-08-27T09:51:15Z-
dc.date.available2014-08-27T09:51:15Z-
dc.date.issued2012-11-28en
dc.identifier.citationNaeem R, Rashid M, Pain A (2012) READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimation. Bioinformatics 29: 391-392. doi:10.1093/bioinformatics/bts684.en
dc.identifier.issn13674803en
dc.identifier.pmid23193222en
dc.identifier.doi10.1093/bioinformatics/bts684en
dc.identifier.urihttp://hdl.handle.net/10754/325436en
dc.description.abstractSummary: READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). Availability: http://cbrc.kaust.edu.sa/readscan Contact: or raeece.naeem@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. 2012 The Author(s).en
dc.language.isoenen
dc.publisherOxford University Pressen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0en
dc.subjectalgorithmen
dc.subjectcarcinomaen
dc.subjectcolorectal tumoren
dc.subjectcomputer programen
dc.subjectFusobacterium nucleatumen
dc.subjectgeneticsen
dc.subjecthigh throughput sequencingen
dc.subjectHuman papillomavirus type 18en
dc.subjectisolation and purificationen
dc.subjectmicrobiologyen
dc.subjectprostate tumoren
dc.subjectvirologyen
dc.subjectvirus genomeen
dc.subjectAlgorithmsen
dc.subjectCarcinomaen
dc.subjectColorectal Neoplasmsen
dc.subjectFusobacterium nucleatumen
dc.subjectGenome, Viralen
dc.subjectHigh-Throughput Nucleotide Sequencingen
dc.subjectHuman papillomavirus 18en
dc.subjectProstatic Neoplasmsen
dc.subjectSoftwareen
dc.titleREADSCAN: A fast and scalable pathogen discovery program with accurate genome relative abundance estimationen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentPathogen Genomics Laboratoryen
dc.identifier.journalBioinformaticsen
dc.identifier.pmcidPMC3562070en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUnidad Académica de Sistemas Arrecifales (Puerto Morelos), Instituto de Ciencias Del Mar y Limnología, Universidad Nacional Autõnoma de México, Puerto Morelos, QR 77580, Mexicoen
dc.contributor.institutionSchool of Natural Sciences, University of California Merced, 5200 North Lake Road, Merced, CA 95343, United Statesen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorNaeem, Raeeceen
kaust.authorRashid, Mamoonen
kaust.authorPain, Arnaben

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