Analysis of Molecular and Cellular Interactions by Combining Network Algorithms and Human Insight

To develop a “human-in-the-loop” system for analysis of Human Cell Atlas data, combining statistically rigorous network algorithms with an interactive web platform for visualization, exploration, and annotation of molecular data.

The Raphael Lab published several resources to advance the “human-in-the-loop” system by combining human intelligence with machine learning to efficiently analyze single-cell sequencing datasets with missing data and low coverage sequencing reads. They developed netNMF, a cell clustering algorithm, and CHISEL, an algorithm developed to improve data coverage in single-cell DNA sequencing. They also developed SCARLET to construct phylogenies from single-nucleotide variants simultaneously and copy number aberrations (CNAs).