Clinical analysis of germline copy number variation in DMD using a non-conjugate hierarchical Bayesian model

Autor: Jonathan F. Freidin, Maxwell Silver, Clayton Stroff, Nigel F. Delaney, Velina Kozareva
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0301 basic medicine
Exome sequencing
lcsh:Internal medicine
congenital
hereditary
and neonatal diseases and abnormalities
lcsh:QH426-470
DNA Copy Number Variations
Computer science
Computational biology
030105 genetics & heredity
03 medical and health sciences
User-Computer Interface
DMD
Genetics
Humans
Multiplex
Logistic normal distribution
Multiplex ligation-dependent probe amplification
Copy-number variation
Genetic Testing
lcsh:RC31-1245
Logit-normal distribution
Saliva
Genotyping
Genetics (clinical)
Illumina dye sequencing
Massive parallel sequencing
High-Throughput Nucleotide Sequencing
Bayes Theorem
Sequence Analysis
DNA
Muscular dystrophy
Human genetics
Copy number variation (CNV)
Muscular Dystrophy
Duchenne
lcsh:Genetics
030104 developmental biology
Germ Cells
Technical Advance
Carrier screening
Zdroj: BMC Medical Genomics
BMC Medical Genomics, Vol 11, Iss 1, Pp 1-12 (2018)
ISSN: 1755-8794
Popis: Background Detection of copy number variants (CNVs) is an important aspect of clinical testing for several disorders, including Duchenne muscular dystrophy, and is often performed using multiplex ligation-dependent probe amplification (MLPA). However, since many genetic carrier screens depend instead on next-generation sequencing (NGS) for wider discovery of small variants, they often do not include CNV analysis. Moreover, most computational techniques developed to detect CNVs from exome sequencing data are not suitable for carrier screening, as they require matched normals, very large cohorts, or extensive gene panels. Methods We present a computational software package, geneCNV (http://github.com/vkozareva/geneCNV), which can identify exon-level CNVs using exome sequencing data from only a few genes. The tool relies on a hierarchical parametric model trained on a small cohort of reference samples. Results Using geneCNV, we accurately inferred heterozygous CNVs in the DMD gene across a cohort of 15 test subjects. These results were validated against MLPA, the current standard for clinical CNV analysis in DMD. We also benchmarked the tool’s performance against other computational techniques and found comparable or improved CNV detection in DMD using data from panels ranging from 4,000 genes to as few as 8 genes. Conclusions geneCNV allows for the creation of cost-effective screening panels by allowing NGS sequencing approaches to generate results equivalent to bespoke genotyping assays like MLPA. By using a parametric model to detect CNVs, it also fulfills regulatory requirements to define a reference range for a genetic test. It is freely available and can be incorporated into any Illumina sequencing pipeline to create clinical assays for detection of exon duplications and deletions. Electronic supplementary material The online version of this article (10.1186/s12920-018-0404-4) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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