Unlocking the Power of Single-Cell DNA Analysis with Simple Software.
Recent advances in molecular biology and microfluidics have enabled us to individually sequence the molecular contents of thousands of single cells. Innovative technologies for single-cell SNV and indel analysis allow researchers to explore single-cell biology by simultaneously identifying the mutation profile within clonal populations, detection of rare subclones, and unambiguous determination of zygosity. These datasets promise to transform our understanding of cellular diversity, but the scale and complexity pose new bottlenecks for data processing and interpretation.
To address these challenges, we have developed intuitive and powerful tools leveraging these rich data and machine learning to optimize data quality and enable insightful interpretation to better understand clonal heterogeneity and tumor evolution.