Bioinformatics for Copy Number Variation Data

Abstract

Copy number variation is known to be an important component of structural variation in the human genome. Greater than 1 kb in size, these gains and losses of genetic material are known to confer risk to many human diseases, both Mendelian and complex. Therefore, the technologies used to detect copy number variation have been quickly improving in both throughput and cost. From comparative genomic hybridization to synthetic high-density oligonucleotide arrays to next-generation sequencing methods, algorithms used to estimate copy number are plentiful. Here we describe a practical introduction to the copy number variation technology and available analysis methods, and demonstrate the analysis flow on an example case.