A backward procedure for change‐point detection with applications to copy number variation detection

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Modified screening and ranking algorithm for copy number variation detection

MOTIVATION Copy number variation (CNV) is a type of structural variation, usually defined as genomic segments that are 1 kb or larger, which present variable copy numbers when compared with a reference genome. The screening and ranking algorithm (SaRa) was recently proposed as an efficient approach for multiple change-points detection, which can be applied to CNV detection. However, some practi...

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De novo detection of copy number variation by co-assembly

MOTIVATION Comparing genomes of individual organisms using next-generation sequencing data is, until now, mostly performed using a reference genome. This is challenging when the reference is distant and introduces bias towards the exact sequence present in the reference. Recent improvements in both sequencing read length and efficiency of assembly algorithms have brought direct comparison of in...

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Family-Based Benchmarking of Copy Number Variation Detection Software

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection s...

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CNVeM: Copy Number Variation Detection Using Uncertainty of Read Mapping

Copy number variations (CNVs) are widely known to be an important mediator for diseases and traits. The development of high-throughput sequencing (HTS) technologies has provided great opportunities to identify CNV regions in mammalian genomes. In a typical experiment, millions of short reads obtained from a genome of interest are mapped to a reference genome. The mapping information can be used...

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ژورنال

عنوان ژورنال: Canadian Journal of Statistics

سال: 2020

ISSN: 0319-5724,1708-945X

DOI: 10.1002/cjs.11535