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

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 pac...

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Published in:	Bioinformatics (Oxford, England) Vol. 30; no. 18; pp. 2670 - 2672
Main Authors:	Boyle, Evan A, O'Roak, Brian J, Martin, Beth K, Kumar, Akash, Shendure, Jay
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 15-09-2014
Subjects:	Algorithms Applications Notes Computational Biology - methods Computer Simulation DNA Probes - genetics Humans Models, Statistical Sequence Analysis - methods
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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 cost-effective targeted sequencing for candidate gene validation and for diagnostic sequencing in a clinical setting. MIPgen is implemented in C++. Source code and accompanying Python scripts are available at http://shendurelab.github.io/MIPGEN/.
AbstractList	Summary 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 cost-effective 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/ . Contact: shendure@uw.edu or boylee@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online. UNLABELLEDMolecular 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 cost-effective targeted sequencing for candidate gene validation and for diagnostic sequencing in a clinical setting. AVAILABILITY AND IMPLEMENTATIONMIPgen is implemented in C++. Source code and accompanying Python scripts are available at http://shendurelab.github.io/MIPGEN/. Summary 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 cost-effective 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/ . Contact: shendure@uw.edu or boylee@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online. 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 cost-effective targeted sequencing for candidate gene validation and for diagnostic sequencing in a clinical setting. MIPgen is implemented in C++. Source code and accompanying Python scripts are available at http://shendurelab.github.io/MIPGEN/.
Author	Boyle, Evan A Kumar, Akash Shendure, Jay Martin, Beth K O'Roak, Brian J
Author_xml	– sequence: 1 givenname: Evan A surname: Boyle fullname: Boyle, Evan A organization: Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA – sequence: 2 givenname: Brian J surname: O'Roak fullname: O'Roak, Brian J organization: Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA – sequence: 3 givenname: Beth K surname: Martin fullname: Martin, Beth K organization: Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA – sequence: 4 givenname: Akash surname: Kumar fullname: Kumar, Akash organization: Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA – sequence: 5 givenname: Jay surname: Shendure fullname: Shendure, Jay organization: Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
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Snippet	Molecular inversion probes (MIPs) enable cost-effective multiplex targeted gene resequencing in large cohorts. However, the design of individual MIPs is a... Summary Molecular inversion probes (MIPs) enable cost-effective multiplex targeted gene resequencing in large cohorts. However, the design of individual MIPs... UNLABELLEDMolecular inversion probes (MIPs) enable cost-effective multiplex targeted gene resequencing in large cohorts. However, the design of individual MIPs... Summary Molecular inversion probes (MIPs) enable cost-effective multiplex targeted gene resequencing in large cohorts. However, the design of individual MIPs...
SourceID	pubmedcentral proquest crossref pubmed
SourceType	Open Access Repository Aggregation Database Index Database
StartPage	2670
SubjectTerms	Algorithms Applications Notes Computational Biology - methods Computer Simulation DNA Probes - genetics Humans Models, Statistical Sequence Analysis - methods
Title	MIPgen: optimized modeling and design of molecular inversion probes for targeted resequencing
URI	https://www.ncbi.nlm.nih.gov/pubmed/24867941 https://search.proquest.com/docview/1560579621 https://pubmed.ncbi.nlm.nih.gov/PMC4155255
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