MutaGeneSys: Estimating individual disease susceptibility based on genome-wide SNP array data

Julia Stoyanovich; Itsik Pe'er

doi:10.1093/bioinformatics/btm587

MutaGeneSys: Estimating individual disease susceptibility based on genome-wide SNP array data

Julia Stoyanovich, Itsik Pe'er

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

Abstract

Summary: We present MutaGeneSys: a system that uses genome-wide genotype data to estimate disease susceptibility. Our system integrates three data sources: the International HapMap project, whole-genome marker correlation data and the Online Mendelian Inheritance in Man (OMIM) database. It accepts SNP data of individuals as query input and delivers disease susceptibility hypotheses even if the original set of typed SNPs is incomplete. Our system is scalable and flexible: it produces population, technology and confidence-specific predictions in interactive time.

Original language	English (US)
Pages (from-to)	440-442
Number of pages	3
Journal	Bioinformatics
Volume	24
Issue number	3
DOIs	https://doi.org/10.1093/bioinformatics/btm587
State	Published - Feb 2008

ASJC Scopus subject areas

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

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10.1093/bioinformatics/btm587

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title = "MutaGeneSys: Estimating individual disease susceptibility based on genome-wide SNP array data",

abstract = "Summary: We present MutaGeneSys: a system that uses genome-wide genotype data to estimate disease susceptibility. Our system integrates three data sources: the International HapMap project, whole-genome marker correlation data and the Online Mendelian Inheritance in Man (OMIM) database. It accepts SNP data of individuals as query input and delivers disease susceptibility hypotheses even if the original set of typed SNPs is incomplete. Our system is scalable and flexible: it produces population, technology and confidence-specific predictions in interactive time.",

author = "Julia Stoyanovich and Itsik Pe'er",

note = "Funding Information: This material is based in part upon work supported by the National Institute of Health grant 5 U54 CA121852-03 and by the National Science Foundation grant IIS-0121239.",

year = "2008",

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doi = "10.1093/bioinformatics/btm587",

language = "English (US)",

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AU - Pe'er, Itsik

N1 - Funding Information: This material is based in part upon work supported by the National Institute of Health grant 5 U54 CA121852-03 and by the National Science Foundation grant IIS-0121239.

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N2 - Summary: We present MutaGeneSys: a system that uses genome-wide genotype data to estimate disease susceptibility. Our system integrates three data sources: the International HapMap project, whole-genome marker correlation data and the Online Mendelian Inheritance in Man (OMIM) database. It accepts SNP data of individuals as query input and delivers disease susceptibility hypotheses even if the original set of typed SNPs is incomplete. Our system is scalable and flexible: it produces population, technology and confidence-specific predictions in interactive time.

AB - Summary: We present MutaGeneSys: a system that uses genome-wide genotype data to estimate disease susceptibility. Our system integrates three data sources: the International HapMap project, whole-genome marker correlation data and the Online Mendelian Inheritance in Man (OMIM) database. It accepts SNP data of individuals as query input and delivers disease susceptibility hypotheses even if the original set of typed SNPs is incomplete. Our system is scalable and flexible: it produces population, technology and confidence-specific predictions in interactive time.

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MutaGeneSys: Estimating individual disease susceptibility based on genome-wide SNP array data

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