MIPgen: Optimized modeling and design of molecular inversion probes for targeted resequencing

Evan A. Boyle, Brian J. O'Roak, Beth K. Martin, Akash Kumar, Jay Shendure

Research output: Contribution to journalArticle

76 Scopus citations

Abstract

Molecular inversion probes (MIPs) enable cost-effective multiplex targeted gene resequencing in large cohorts. However, the design of individual MIPs is a critical parameter governing the performance of this technology with respect to capture uniformity and specificity. MIPgen is a user-friendly package that simplifies the process of designing custom MIP assays to arbitrary targets. New logistic and SVM-derived models enable in silico predictions of assay success, and assay redesign exhibits improved coverage uniformity relative to previous methods, which in turn improves the utility of MIPs for costeffective targeted sequencing for candidate gene validation and for diagnostic sequencing in a clinical setting.

Availability and implementation: MIPgen is implemented in C++. Source code and accompanying Python scripts are available at http://shendurelab.github.io/MIPGEN/.

Original languageEnglish (US)
Pages (from-to)2670-2672
Number of pages3
JournalBioinformatics
Volume30
Issue number18
DOIs
StatePublished - 2014

ASJC Scopus subject areas

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

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