Evidence map›Paper›PMID 24597945›Full record

ArticleBMC genomics2014

DB2: a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads.

Gökhan Yavaş, Mehmet Koyutürk, Meetha P Gould, Sarah McMahon, Thomas LaFramboise

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In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Gökhan Yavaş
Mehmet Koyutürk
Meetha P Gould
Sarah McMahon
Thomas LaFramboiseDepartment of Genetics and Genome Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA. thomas.laframboise@case.edu.

Funding

TRAINING IN COMPUTATIONAL GENOMIC EPIDEMIOLOGY OF CANCERR25CA094186 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI LI, LI · 2002 to 2016
$6.8M
Enhancing Genome-Wide Association Studies via Integrative Network AnalysisR01LM011247 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI KOYUTURK, MEHMET · 2012 to 2015
$1.3M
A genomic survey of allele-specific selection in tumor ampliconsR01CA131341 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI LAFRAMBOISE, THOMAS LOUIS, PE'ER, ITSHACK G · 2008 to 2011
$1.2M
NCI NIH HHS R01 CA131341NCI NIH HHS R25 CA094186NLM NIH HHS R01 LM011247
6 · The paper itself

Abstract

backgroundWith the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified variants. In this paper, we propose a new method, Distribution Based detection of Duplication Boundaries (DB2), for accurate detection of tandem duplication breakpoints, an important class of structural variation, with high precision and recall.

resultsOur computational experiments on simulated data show that DB2 outperforms state-of-the-art methods in terms of finding breakpoints of tandem duplications, with a higher positive predictive value (precision) in calling the duplications' presence. In particular, DB2's prediction of tandem duplications is correct 99% of the time even for very noisy data, while narrowing down the space of possible breakpoints within a margin of 15 to 20 bps on the average. Most of the existing methods provide boundaries in ranges that extend to hundreds of bases with lower precision values. Our method is also highly robust to varying properties of the sequencing library and to the sizes of the tandem duplications, as shown by its stable precision, recall and mean boundary mismatch performance. We demonstrate our method's efficacy using both simulated paired-end reads, and those generated from a melanoma sample and two ovarian cancer samples. Newly discovered tandem duplications are validated using PCR and Sanger sequencing.

conclusionsOur method, DB2, uses discordantly aligned reads, taking into account the distribution of fragment length to predict tandem duplications along with their breakpoints on a donor genome. The proposed method fine tunes the breakpoint calls by applying a novel probabilistic framework that incorporates the empirical fragment length distribution to score each feasible breakpoint. DB2 is implemented in Java programming language and is freely available at http://mendel.gene.cwru.edu/laframboiselab/software.php.

Indexed as

AlgorithmsDNA BreaksGene DuplicationGenomeBase Pair MismatchFemalefms-Like Tyrosine Kinase 3Gene LibraryHigh-Throughput Nucleotide SequencingHumansOvarian NeoplasmsSequence Analysis, DNASoftwareFLT3 protein, humanfms-Like Tyrosine Kinase 3

Identifiers

PMID24597945
PMCPMC4234483

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.