Challenges in unsupervised clustering of single-cell RNA-seq data View Full Text


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Article Info

DATE

2019-01-07

AUTHORS

Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg

ABSTRACT

Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the analysis of these data, as it is used to identify putative cell types. However, there are many challenges involved. We discuss why clustering is a challenging problem from a computational point of view and what aspects of the data make it challenging. We also consider the difficulties related to the biological interpretation and annotation of the identified clusters. More... »

PAGES

1

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    http://scigraph.springernature.com/pub.10.1038/s41576-018-0088-9

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    http://dx.doi.org/10.1038/s41576-018-0088-9

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30617341


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