scClassify: hierarchical classification of cells

Lin, Y.; Cao, Y.; Kim, H. J.; Salim, A.; Speed, T. P.; Lin, D.; Yang, P.; Yang, J. Y. H.

doi:10.1101/776948

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bioRxiv · 10.1101/776948

scClassify: hierarchical classification of cells

Lin, Y.·Cao, Y.·Kim, H. J.·Salim, A.·Speed, T. P.·Lin, D.·Yang, P.·Yang, J. Y. H.

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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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Lin, Y., Cao, Y., Kim, H. J., Salim, A., Speed, T. P., Lin, D., Yang, P., Yang, J. Y. H.. 2019-09-23. scClassify: hierarchical classification of cells. https://doi.org/10.1101/776948

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