Exploration and visualization of next-generation sequencing data are crucial for clinical diagnostics. Software allowing simultaneous visualization of multiple regions of interest coupled with dynamic heuristic filtering of genetic aberrations is, however, lacking. Therefore, the authors developed the web application SNPitty that allows interactive visualization and interrogation of variant call format files by using B-allele frequencies of single-nucleotide polymorphisms and single-nucleotide variants, coverage metrics, and copy numbers analysis results. SNPitty displays variant alleles and allelic imbalances with a focus on loss of heterozygosity and copy number variation using genome-wide heterozygous markers and somatic mutations. In addition, SNPitty is capable of generating predefined reports that summarize and highlight disease-specific targets of interest. SNPitty was validated for diagnostic interpretation of somatic events by showcasing a serial dilution series of glioma tissue. Additionally, SNPitty is demonstrated in four cancer-related scenarios encountered in daily clinical practice and on whole-exome sequencing data of peripheral blood from a Down syndrome patient. SNPitty allows detection of loss of heterozygosity, chromosomal and gene amplifications, homozygous or heterozygous deletions, somatic mutations, or any combination thereof in regions or genes of interest. Furthermore, SNPitty can be used to distinguish molecular relationships between multiple tumors from a single patient. On the basis of these data, the authors demonstrate that SNPitty is robust and user friendly in a wide range of diagnostic scenarios.

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Persistent URL dx.doi.org/10.1016/j.jmoldx.2017.11.011, hdl.handle.net/1765/104875
Journal The Journal of Molecular Diagnostics
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Citation
van Riet, J, Krol, N.M.G, Atmodimedjo, P.N, Brosens, E, van IJcken, W.F.J, Jansen, M.P.H.M, … van de Werken, H.J.G. (2018). SNPitty: An Intuitive Web Application for Interactive B-Allele Frequency and Copy Number Visualization of Next-Generation Sequencing Data. The Journal of Molecular Diagnostics, 20(2), 166–176. doi:10.1016/j.jmoldx.2017.11.011