Anna Gilbert,​ ​​LSA's Herman​ ​​H. ​Goldstine Collegiate Professor of Mathematics, has received funding from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation, for her project “Identifying genetic markers: dimension reduction and feature selection for sparse data.” Her project is part of a large effort involving collaborative computational tools to support and contribute to efforts to develop the Human Cell Atlas. The goal of the Human Cell Atlas project is to create a shared, open reference atlas of all cells in the healthy human body as a resource for studies of health and disease. 

​Here's how Anna describes her project:

One of the​ ​​ways that scientists participating in the Human Cell Atlas will gather data is​ ​​through ​single​-cell RNA ​sequencing (scRNA-seq). The analysis, however, of scRNA-seq data​ ​​comes with novel biological and algorithmic challenges. The data ​have​​ ​high dimensionality​​ ​and​​ ​are ​not necessarily in distinct clusters (indeed, some cell types exist along a continuum or developmental trajectory). In addition, data values are missing.​ ​​So t​o​ analyze this data, we must adjust our dimension​-​reduction algorithms​ ​​by​ ​either filling​​ ​in the​ ​​missing ​values or quantifying the impact of the missing values.​ ​​Our​ work​​,​ funded by the Chan Zuckerberg Initiative,​​ ​will leverage modern, sparsity-based machine learning methods and apply them to dimension reduction, marker selection, and data imputation for scRNA-seq data.