Abstract：
:We present single-cell interpretation via multikernel learning (SIMLR), an analytic framework and software which learns a similarity measure from single-cell RNA-seq data in order to perform dimension reduction, clustering and visualization. On seven published data sets, we benchmark SIMLR against state-of-the-art methods. We show that SIMLR is scalable and greatly enhances clustering performance while improving the visualization and interpretability of single-cell sequencing data.
journal_name
Nat Methodsjournal_title
Nature methodsauthors
Wang B,Zhu J,Pierson E,Ramazzotti D,Batzoglou Sdoi
10.1038/nmeth.4207subject
Has Abstractpub_date
2017-04-01 00:00:00pages
414-416issue
4eissn
1548-7091issn
1548-7105pii
nmeth.4207journal_volume
14pub_type
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