SNPPicker: High quality tag SNP selection across multiple populations

Hugues Sicotte, David N. Rider, Gregory A. Poland, Neelam Dhiman, Jean-Pierre Kocher

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Background: Linkage Disequilibrium (LD) bin-tagging algorithms identify a reduced set of tag SNPs that can capture the genetic variation in a population without genotyping every single SNP. However, existing tag SNP selection algorithms for designing custom genotyping panels do not take into account all platform dependent factors affecting the likelihood of a tag SNP to be successfully genotyped and many of the constraints that can be imposed by the user.Results: SNPPicker optimizes the selection of tag SNPs from common bin-tagging programs to design custom genotyping panels. The application uses a multi-step search strategy in combination with a statistical model to maximize the genotyping success of the selected tag SNPs. User preference toward functional SNPs can also be taken into account as secondary criteria. SNPPicker can also optimize tag SNP selection for a panel tagging multiple populations. SNPPicker can optimize custom genotyping panels including all the assay-specific constraints of Illumina's GoldenGate and Infinium assays.Conclusions: A new application has been developed to maximize the success of custom multi-population genotyping panels. SNPPicker also takes into account user constraints including options for controlling runtime. Perl Scripts, Java source code and executables are available under an open source license for download at http://mayoresearch.mayo.edu/mayo/research/biostat/software.cfm.

Original languageEnglish (US)
Article number129
JournalBMC Bioinformatics
Volume12
DOIs
StatePublished - May 2 2011

Fingerprint

Bins
Single Nucleotide Polymorphism
Assays
Tagging
Population
Optimise
Maximise
Linkage Disequilibrium
JavaScript
Genetic Variation
User Preferences
Search Strategy
Open Source
Statistical Model
Likelihood
Statistical Models
Licensure
Software
Dependent
Research

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics
  • Structural Biology

Cite this

SNPPicker : High quality tag SNP selection across multiple populations. / Sicotte, Hugues; Rider, David N.; Poland, Gregory A.; Dhiman, Neelam; Kocher, Jean-Pierre.

In: BMC Bioinformatics, Vol. 12, 129, 02.05.2011.

Research output: Contribution to journalArticle

Sicotte, Hugues ; Rider, David N. ; Poland, Gregory A. ; Dhiman, Neelam ; Kocher, Jean-Pierre. / SNPPicker : High quality tag SNP selection across multiple populations. In: BMC Bioinformatics. 2011 ; Vol. 12.
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