Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data.

ABSTRACT: Remarkable advances in single cell genomics have presented unique challenges and opportunities for interrogating a wealth of biomedical inquiries. High dimensional genomic data are inherently complex because of intertwined relationships among the genes. Existing methods, including emerging deep learning-based approaches, do not consider the underlying biological characteristics during data processing, which greatly compromises the performance of data analysis and hinders the maximal utilization of state-of-the-art genomic techniques. In this work, we develop an entropy-based cartography strategy to contrive the high dimensional gene expression data into a configured image format, referred to as genomap, with explicit integration of the genomic interactions. This unique cartography casts th

SUBMITTER: Islam MT 

PROVIDER: S-EPMC9908983 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature