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

Raeece Naeem; Mamoon Rashid; Arnab Pain

doi:10.1093/bioinformatics/bts684

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

Raeece Naeem, Mamoon Rashid, Arnab Pain

Research output: Contribution to journal › Article › peer-review

44 Scopus citations

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

Original language	English (US)
Pages (from-to)	391-392
Number of pages	2
Journal	Bioinformatics
Volume	29
Issue number	3
DOIs	https://doi.org/10.1093/bioinformatics/bts684
State	Published - Nov 28 2012

ASJC Scopus subject areas

Biochemistry
Computational Theory and Mathematics
Computational Mathematics
Molecular Biology
Statistics and Probability
Computer Science Applications

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10.1093/bioinformatics/bts684

https://repository.kaust.edu.sa/bitstream/10754/325436/1/Article-Bioinforma-READSCAN_A-2013.pdf

Cite this

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title = "READSCAN: A fast and scalable pathogen discovery program with accurate genome relative abundance estimation",

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",

author = "Raeece Naeem and Mamoon Rashid and Arnab Pain",

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AU - Rashid, Mamoon

AU - Pain, Arnab

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PY - 2012/11/28

Y1 - 2012/11/28

N2 - 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

AB - 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

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

Abstract

ASJC Scopus subject areas

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