About TESV

We described copy number variation analysis workflow here based on copy number variation analysis pipeline by Genome Data Commons (GDC).

We also referenced copy number inference pipeline by GenePattern. We showed a tumor-normal different CNV analysis workflow via public TCGA breast cancer (BRCA) CNV paired-sample data derived from Affymetrix SNP 6.0 array data.

Here, we reviewed SV-related, computational and available tools publicly published in PubMed database (https://www.ncbi.nlm.nih.gov/pubmed), GitHub (https://github.com/), SourceForge (https://sourceforge.net/), CRAN (https://cran.r-project.org/) and Bioconductor (http://bioconductor.org/) over the past two decades.

These computational tools mainly depend on the development of Sanger sequencing, microarray, next-generation sequencing (NGS) and third-generation sequencing for the identification of high-resolution SV.

SV could be also divided into balanced or unbalanced changes in DNA content according to the variation pattern. The unbalanced alterations of DNA include duplications, insertions and deletions of DNA base fragments, as well as balanced events consist of inversions and inter and intrachromosomal translocations.