title: GiniClust: detecting rare cell types from single-cell gene expression data with Gini index.
abstract: High-throughput single-cell technologies have great potential to discover new cell types; however, it remains challenging to detect rare cell types that are distinct from a large population. We present a novel computational method, called GiniClust, to overcome this challenge. Validation against a benchmark dataset indicates that GiniClust achieves high sensitivity and specificity. Application of GiniClust to public single-cell RNA-seq datasets uncovers previously unrecognized rare cell types, including Zscan4-expressing cells within mouse embryonic stem cells and hemoglobin-expressing cells in the mouse cortex and hippocampus. GiniClust also correctly detects a small number of normal cells that are mixed in a cancer cell population.
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.|Boston Children's Hospital, Boston, MA, 02115, USA.
authors.forename: Lan
authors.initials: L
authors.lastname: Jiang
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.|Department of Computer Science and Technology, Tongji University, Shanghai, China.
authors.forename: Huidong
authors.initials: H
authors.lastname: Chen
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
authors.forename: Luca
authors.initials: L
authors.lastname: Pinello
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA. gcyuan@jimmy.harvard.edu.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. gcyuan@jimmy.harvard.edu.|Harvard Stem Cell Institute, Cambridge, MA, 02138, USA. gcyuan@jimmy.harvard.edu.
authors.forename: Guo-Cheng
authors.initials: GC
authors.lastname: Yuan
mesh_terms: D000818:Animals; D019070:Cell Lineage / Q000235:genetics*; D002525:Cerebellar Cortex / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics*; D006454:Hemoglobins / Q000096:biosynthesis; D059014:High-Throughput Nucleotide Sequencing; D006624:Hippocampus / Q000378:metabolism; D051379:Mice; D000066450:Mouse Embryonic Stem Cells / Q000378:metabolism; D012313:RNA / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods; D059010:Single-Cell Analysis
chemical_list: D006454:Hemoglobins; D012313:RNA
keywords: Clustering; Gini index; RNA-seq; Rare cell type; Single-cell analysis; qPCR