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GiniClust2: a cluster-aware, weighted ensemble clustering method for cell-type detection
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GiniClust2: a cluster-aware, weighted ensemble clustering method for cell-type detection
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Journal Article
GiniClust2: a cluster-aware, weighted ensemble clustering method for cell-type detection
2018
Overview
Single-cell analysis is a powerful tool for dissecting the cellular composition within a tissue or organ. However, it remains difficult to detect rare and common cell types at the same time. Here, we present a new computational method, GiniClust2, to overcome this challenge. GiniClust2 combines the strengths of two complementary approaches, using the Gini index and Fano factor, respectively, through a cluster-aware, weighted ensemble clustering technique. GiniClust2 successfully identifies both common and rare cell types in diverse datasets, outperforming existing methods. GiniClust2 is scalable to large datasets.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
