SMILE: Mutual Information Learning for Integration of Single Cell Omics Data Yang Xu, Priyojit Das, Rachel Patton McCord UT-ORNL Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN Biochemistry & Cellular and Molecular Biology Department, University of Tennessee, Knoxville, TN As increasing numbers of single-cell sequencing datasets are available, data integration becomes a key research domain for understanding a complex cellular system from different angles, but also presents a new challenge for data analysis. Here, We present a deep clustering algorithm that learns discriminative representation for single-cell data via maximizing mutual information, SMILE (Single-cell Mutual Information Learning). SMILE successfully integrates multi-source single-cell transcriptome data and can also integrate single-cell ATAC-seq, RNA-seq, DNA methylation, and Hi-C data generated by the latest joint profiling technologies.
University of Tennessee, Knoxville
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