Current analysis platforms and methods for detecting copy number variation

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Current analysis platforms and methods for detecting copy number variation.

Copy number variation (CNV), generated through duplication or deletion events that affect one or more loci, is widespread in the human genomes and is often associated with functional consequences that may include changes in gene expression levels or fusion of genes. Genome-wide association studies indicate that some disease phenotypes and physiological pathways might be impacted by CNV in a sma...

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Detecting differential copy number variation between groups of samples.

We present a method to detect copy number variants (CNVs) that are differentially present between two groups of sequenced samples. We use a finite-state transducer where the emitted read depth is conditioned on the mappability and GC-content of all reads that occur at a given base position. In this model, the read depth within a region is a mixture of binomials, which in simulations matches the...

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BIRC5 Genomic Copy Number Variation in Early-Onset Breast Cancer

Background: Baculoviral inhibitor of apoptosis repeat-containing 5 (BIRC5) gene is an inhibitor of apoptosis that expresses in human embryonic tissues but it is absent in most healthy adult tissues. The copy number of BIRC5 has been indicated to be highly increased in tumor tissues; however, its association with the age of onset in breast cancer is not well understood. Methods: Forty tumor tiss...

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Genome-Wide Mapping of Copy Number Variation in Humans: Comparative Analysis of High Resolution Array Platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridizati...

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Elaborate downstream methods are required to analyze large microarray data-sets. At times, where the end goal is to look for relationships between (or patterns within) different subgroups or even just individual samples, large data-sets must first be filtered using statistical thresholds in order to reduce their overall volume. As an example, in anthropological microarray studies, such ‘dimensi...

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ژورنال

عنوان ژورنال: Physiological Genomics

سال: 2013

ISSN: 1094-8341,1531-2267

DOI: 10.1152/physiolgenomics.00082.2012