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@ARTICLE{Kiselev2019-bt,
  title    = "Challenges in unsupervised clustering of single-cell {RNA-seq}
              data",
  author   = "Kiselev, Vladimir Yu and Andrews, Tallulah S and Hemberg, Martin",
  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.",
  journal  = "Nat. Rev. Genet.",
  volume   =  20,
  number   =  5,
  pages    = "273--282",
  month    =  may,
  year     =  2019,
  language = "en"
}