Literature DB >> 20876606

SLOPE: a quick and accurate method for locating non-SNP structural variation from targeted next-generation sequence data.

Haley J Abel1, Eric J Duncavage, Nils Becker, Jon R Armstrong, Vincent J Magrini, John D Pfeifer.   

Abstract

MOTIVATION: Targeted 'deep' sequencing of specific genes or regions is of great interest in clinical cancer diagnostics where some sequence variants, particularly translocations and indels, have known prognostic or diagnostic significance. In this setting, it is unnecessary to sequence an entire genome, and target capture methods can be applied to limit sequencing to important regions, thereby reducing costs and the time required to complete testing. Existing 'next-gen' sequencing analysis packages are optimized for efficiency in whole-genome studies and are unable to benefit from the particular structure of targeted sequence data.
RESULTS: We developed SLOPE to detect structural variants from targeted short-DNA reads. We use both real and simulated data to demonstrate SLOPE's ability to rapidly detect insertion/deletion events of various sizes as well as translocations and viral integration sites with high sensitivity and low false discovery rate. AVAILABILITY: Binary code available at http://www-genepi.med.utah.edu/suppl/SLOPE/index.html

Entities:  

Mesh:

Year:  2010        PMID: 20876606     DOI: 10.1093/bioinformatics/btq528

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  31 in total

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3.  Hybrid capture and next-generation sequencing identify viral integration sites from formalin-fixed, paraffin-embedded tissue.

Authors:  Eric J Duncavage; Vincent Magrini; Nils Becker; Jon R Armstrong; Ryan T Demeter; Todd Wylie; Haley J Abel; John D Pfeifer
Journal:  J Mol Diagn       Date:  2011-05       Impact factor: 5.568

Review 4.  Detection of structural DNA variation from next generation sequencing data: a review of informatic approaches.

Authors:  Haley J Abel; Eric J Duncavage
Journal:  Cancer Genet       Date:  2013-11-20

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Review 6.  Systems genetics in "-omics" era: current and future development.

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9.  Accurate and exact CNV identification from targeted high-throughput sequence data.

Authors:  Alex S Nord; Ming Lee; Mary-Claire King; Tom Walsh
Journal:  BMC Genomics       Date:  2011-04-12       Impact factor: 3.969

10.  Genomic analysis of inherited breast cancer among Palestinian women: Genetic heterogeneity and a founder mutation in TP53.

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Journal:  Int J Cancer       Date:  2017-05-19       Impact factor: 7.396

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