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Computational Tool Advances Understanding of COVID-19 and Alzheimer’s Disease

Yale Public Health Magazine, Yale Public Health: Fall 2023
by Jane E. Dee


Chang Su, PhD ’23 (biostatistics), and colleagues at Yale School of Public Health and Emory University have developed an innovative computational tool to characterize the functional organization of genes in cell types using single-cell RNA-sequencing data.

The statistical model they developed, named CS-CORE, addresses the key challenges in single-cell data, including high sparsity and noises. CS-CORE can better identify the biological functions and pathways in cell types in human tissues, such as brain and blood, than existing methods in systematic benchmarking and real data analyses, said Su, assistant professor at Emory University. CS-CORE was developed during Su’s PhD studies under the supervision of Hongyu Zhao, Ira V. Hiscock Professor of Biostatistics, and Professor of Genetics and Statistics and Data Science.

When applied to single-cell studies on Alzheimer's disease and COVID-19, CS-CORE uncovered dysregulations in biological pathways in cell types that advanced the understanding of the disease mechanisms.

Su was awarded the JXTX + CSHL Biology of Genomes scholarship and presented CS-CORE in a talk at The Biology of Genomes meeting at Cold Spring Harbor Laboratory in May 2023. CS-CORE was jointly developed by The Zhao lab: Hongyu Zhao, and lab members Chang Su, Zichun Xu, Xinning Shan, Biao Cai, and Emma Jingfei Zhang of Emory University. Their paper, “Cell-type-specific co-expression inference from single cell RNA-sequencing data,” was published in Nature Communications.

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