Structural Variation Detection Analysis
Structural Variations (SVs) are the various genetic changes or at times mutations in the chromosomal structure caused by a variety of rearrangements. There are hundreds of thousands of these SVs in each genome and are responsible for genetic diversity, phenotypic traits and diseases susceptibility. Most of the last two decades focused on detecting single nucleotide variations (SNPs) as these point mutations are responsible for causing 85% of Mendelian diseases. Genomics community has been recently focused on developing a better understanding of structural variations and their role in phenotypes and diseases. Detection of large mutations >1kb continue to elude most of conventional methods of detection. Structural Variations (SVs) using Next generation sequencing is fast becoming the method of choice. NGS data analysis for large and complex SV detection, however, is extremely challenging. A recent review by Ye et all (2016) lists at least 25 different software for SV detection.