Advancements in high-throughput sequencing technologies have uncovered tremendous genetic, epigenetic, and transcriptional heterogeneity in chronic lymphocytic leukemia (CLL) but its impact on clinical course is not well understood. I have established a close collaboration with the Wu lab at the Dana-Farber Cancer Institute, where I have focused on developing and applying bioinformatics methods for assessing variability of single cell gene expression, calling mutations from single cell qt-qPCR data, differential expression and gene set enrichment tests for both bulk and single cell, RNA-sequencing and targeted qt-qPCR data. Our collaboration has led to many scientific findings that contribute to a more complete understanding of CLL.

While heterogeneity within cellular systems has long been widely recognized, only recently have technological advances enabled measurements to be made on a single cell level. Applying traditional bulk analysis methods on single cells has met with varied degrees of success due to the high levels of technical as well as biological stochasticity and noise inherent in single cell measurements. Therefore, novel statistical methods are needed to identify and characterize heterogeneity in single cells. In the Kharchenko lab, I have focused on developing methods for analyzing single cell data, including differential expression analysis methods that takes into account sources of technical noise inherent to single cell RNA-seq data, clustering methods to identify pathways and gene sets that exhibit coordinated variability, and methods for spatial placement of cell subpopulations based on expression signatures. This work has led to the development of various statistical methods available as software for the scientific community.

Women are underrepresented in science, technology, engineering, and math (STEM) fields. Improving the representation of women in STEM is pertinent to workplace diversity, gender equality, and American innovation. To help address this issue, I have been involved in a number of outreach efforts. I was the lead software engineer for the BioHazardz 3D video games, which teach students the fundamentals of protein evolution through an intuitive and attractive gaming environment. I founded the 501(c)3 non-profit CuSTEMized and developed the website, software, graphics, and content to enable parents to generate and download free personalized motivational ebooks to help girls envision themselves in science, technology, engineering, and math. I am the co-chair of the Harvard Graduate Women in Science and Engineering student group. I manage and lead organization of networking, professional development, and mentoring events for women in natural sciences, social sciences, and engineering at Harvard University.