Possibilities and Limitations of CNV Interpretation Software and Algorithms in Homo Sapiens

Background: Technical advances and cost reduction have allowed for the worldwide popularity of array platforms. Otherwise called “molecular karyotyping”, it yields a large amount of CNV data, which is useless without interpretation. Objective: This study aims to review existing CNV interpretation software and algorithms to reveal their possibilities and limitations. Results: Open and user-friendly CNV interpretation software is limited to several options, which mostly do not allow for cross-interpretation. Many algorithms are generally based on the Database of Genomic Variants, CNV size, inheritance data, and disease databases, which currently seem insufficient. Conclusion: The analysis of CNV interpretation software and algorithms resulted in a conclusion that it is necessary to expand the existing algorithms of CNV interpretation and at least include pathway and expression data. A user-friendly freely available CNV interpretation software, based on the expanded algorithms, is yet to be created.