Journal article
scClassify: sample size estimation and multiscale classification of cells using single and multiple reference
Y Lin, Y Cao, HJ Kim, A Salim, TP Speed, DM Lin, P Yang, JYH Yang
Molecular Systems Biology | SPRINGERNATURE | Published : 2020
Abstract
Automated cell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalise on the large collection of well-annotated scRNA-seq datasets, we developed scClassify, a multiscale classification framework based on ensemble learning and cell type hierarchies constructed from single or multiple annotated datasets as references. scClassify enables the estimation of sample size required for accurate classification of cell types in a cell type hierarchy and allows joint classification of cells when multiple references are available. We show that scClassify consistently performs better than other supervised cell type classification methods across 1..
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Awarded by University of Sydney
Funding Acknowledgements
The authors thank all their colleagues, particularly at The University of Sydney, School of Mathematics and Statistics, for their support and intellectual engagement. We also thank Andy Tran for testing the package. The following sources of funding for each author, and for the manuscript preparation, are gratefully acknowledged: Australian Research Council Discovery Project Grant (DP170100654) to JYHY and PY; Discovery Early Career Researcher Award (DE170100759) and Australia National Health and Medical Research Council (NHMRC) Investigator Grant (APP1173469) to PY; Australia NHMRC Career Developmental Fellowship (APP1111338) to JYHY; Research Training Program Tuition Fee Offset and Stipend Scholarship and Chen Family Research Scholarship to YL; Australian Research Council (ARC) Postgraduate Research Scholarship and Children's Medical Research Institute Postgraduate Scholarship to HJK; University of Sydney Postgraduate Award Stipend Scholarship to YC; and NIH grant (R21DC015107) to DML. The funding source had no role in the study design; in the collection, analysis and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.