Molecular Systems BiologyBioinformaticsPeer-reviewed journal article
scClassify: hierarchical classification of cells
Yingxin LiniD, Yue CaoiD, Hani Jieun KimiD, Agus SalimiD, Terence Paul SpeediD, Dave Lin, Pengyi YangiD, Jean Yee Hwa YangiD
Abstract
Cell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalize on the large collections of well-annotated scRNA-seq datasets, we present scClassify, a hierarchical classification framework based on ensemble learning. scClassify can identify cells from published scRNA-seq datasets more accurately and more finely than in the original publications. We also estimate the cell number needed for accurate classification anywhere in a cell type hierarchy.
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