Congrats to Xiaoqiao Chen for her new paper on using active support vector machines (activeSVM) to discover minimal gene sets

Check out the new paper here!

Xiaoqiao’s method assembles minimal lists of highly informative genes using an iterative SVM approach. Each iteration uses only a small numbers of cells and genes for computation. She uses a clever ‘active’ strategy to prioritize cells and genes that are most commonly misclassified, thus ensuring that selected genes improve classification on outliers. Because only a small number of cells and genes are used at each step, the process is very memory efficient, and allows her to compute over huge datasets (>1M cells) in a little over an hour (compared to days for other algorithms).