Publications

BMC methods. 2024-11-04; 1.

Discovery of optimal cell type classification marker genes from single cell RNA sequencing data

Liu A, Peng B, Pankajam AV, Duong TE, Pryhuber G, Scheuermann RH, Zhang Y

PMID: 40893796

Abstract

The use of single cell/nucleus RNA sequencing (scRNA-seq) technologies that quantitively describe cell transcriptional phenotypes is revolutionizing our understanding of cell biology, leading to new insights in cell type identification, disease mechanisms, and drug development. The tremendous growth in scRNA-seq data has posed new challenges in efficiently characterizing data-driven cell types and identifying quantifiable marker genes for cell type classification. The use of machine learning and explainable artificial intelligence has emerged as an effective approach to study large-scale scRNA-seq data.

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