Statistical Bioinformatics Seminar Series: Zhang

Title: Single cell multi-omics data integration and evaluation 

Speaker: Dr Xiuwei Zhang (Georgia Institute of Technology) 

Abstract: Single cell data integration methods aim to integrate cells across data
batches and modalities, and data integration tasks can be categorized into horizontal,
vertical, diagonal, and mosaic integration.  Although many methods have been developed
for data integration, there are scenarios that need special precaution, for example,
when the datasets come from different patients under varying medical conditions.  Also,
quantitatively evaluating the performance of computational methods in single cell
genomics has been a challenge due to the lack of ground truth information.  I will
present scDisInFact, a method to integrate scRNA-seq data from different patients while
disentangling batch effects from biological variations across batches associated with
patient conditions; and scMultiSim, a simulator for multi-modality single-cell data that
can be used to benchmark a range of computational methods including data integration
methods.  

About the speaker: Xiuwei Zhang is an Assistant Professor and a J.Z.  Liang Early Career
Professor at the School of Computational Science & Engineering at Georgia Tech.  She
obtained her PhD in computer science from EPFL (École Polytechnique Fédérale de
Lausanne) in Switzerland, and conducted postdoctoral research at Cambridge, UK and UC
Berkeley.  Her research focuses on developing methods to analyze single cell genomics
data, including methods to study cell temporal dynamics, to perform data integration and
to infer molecular interactions.  She is a recipient of an NSF CAREER Award and the NIH
Maximizing Investigators’ Research Award.