Copy Number Variation.

TitreCopy Number Variation.
Publication TypeJournal Article
Year of Publication2018
AuthorsMacé, A, Kutalik, Z, Valsesia, A
JournalMethods in molecular biology
Volume1793
Pagination231-258
Date Published06/2018
DOI10.1007/978-1-4939-7868-7_14
ISSN1940-6029
Mots-clésCopy number variation, Deletion, DNA, Duplication, genome-wide association studies, Human disease, human genetics, Structural variation
Abstract

Differences between genomes can be due to single nucleotide variants (SNPs), translocations, inversions and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 250 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease or phenotypic traits.While the link between SNPs and disease susceptibility has been well studied, to date there are still very few published CNV genome-wide association studies; probably owing to the fact that CNV analysis remains a slightly more complex task than SNP analysis (both in term of bioinformatics workflow and uncertainty in the CNV calling leading to high false positive rates and unknown false negative rates). This chapter aims at explaining computational methods for the analysis of CNVs, ranging from study design, data processing and quality control, up to genome-wide association study with clinical traits.

Alternate URL

http://www.ncbi.nlm.nih.gov/pubmed/29876900?dopt=Abstract

WOS ID (UT)

000443462700015

Alternate JournalMethods Mol. Biol.
Citation Key / SERVAL ID8956
Peer reviewRefereed
PubMed ID29876900
                         

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