references.bib

@article{Wolf2018,
  author   = {Wolf, F. Alexander
              and Angerer, Philipp
              and Theis, Fabian J.},
  title    = {SCANPY: large-scale single-cell gene expression data analysis},
  journal  = {Genome Biology},
  year     = {2018},
  month    = {Feb},
  day      = {06},
  volume   = {19},
  number   = {1},
  pages    = {15},
  abstract = {Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells (https://github.com/theislab/Scanpy). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices (https://github.com/theislab/anndata).},
  issn     = {1474-760X},
  doi      = {10.1186/s13059-017-1382-0},
  url      = {https://doi.org/10.1186/s13059-017-1382-0}
}