SEAN: SNP prediction and display program utilizing EST sequence clusters

被引：25

作者：

Huntley, D ^{[1
]}

Baldo, A

Johri, S

Sergot, M

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Ctr Bioinformat, Div Mol Biosci, London SW7 2AZ, England

[2] Univ London Imperial Coll Sci Technol & Med, Ctr Mol Microbiol & Infect, Div Invest Sci, London SW7 2AZ, England

[3] Univ London Imperial Coll Sci Technol & Med, Dept Comp, London SW7 2AZ, England

[4] New York State Agr Exptl Stn, USDA ARS, Plant Genet Resources Unit, Geneva, NY 14456 USA

来源：

BIOINFORMATICS | 2006年 / 22卷 / 04期

关键词：

D O I：

10.1093/bioinformatics/btk006

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.

引用

页码：495 / 496

页数：2

共 12 条

[1] Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP [J].