Title |
Biological relevance of CNV calling methods using familial relatedness including monozygotic twins
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Published in |
BMC Bioinformatics, April 2014
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DOI | 10.1186/1471-2105-15-114 |
Pubmed ID | |
Authors |
Christina A Castellani, Melkaye G Melka, Andrea E Wishart, M Elizabeth O Locke, Zain Awamleh, Richard L O’Reilly, Shiva M Singh |
Abstract |
Studies involving the analysis of structural variation including Copy Number Variation (CNV) have recently exploded in the literature. Furthermore, CNVs have been associated with a number of complex diseases and neurodevelopmental disorders. Common methods for CNV detection use SNP, CNV, or CGH arrays, where the signal intensities of consecutive probes are used to define the number of copies associated with a given genomic region. These practices pose a number of challenges that interfere with the ability of available methods to accurately call CNVs. It has, therefore, become necessary to develop experimental protocols to test the reliability of CNV calling methods from microarray data so that researchers can properly discriminate biologically relevant data from noise. |
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