CellRank 1.1.0 (2020-11-17)#


  • Fix not vendorizing correct msmtools which sometimes densified sparse matrix.

  • Bump scanpy version requirement to 1.6 to fix plotting PR 444.


  • cellrank.tl.lineage_drivers() computes p-values for the identified driver genes now, using either a Fisher-transformation to approximate the distribution of the test statistic under the null hypothesis or an exact, permutation based test. Corrects for multiple-testing.

  • cellrank.tl.kernels.VelocityKernel.compute_transition_matrix() now allows different metrics to be used to compare velocity vectors with expression-differences across neighboring cells. We add cosine-correlation and dot-product schemes and we allow the user to input their own scheme. It has been shown recently by [Li et al., 2021] that the choice of metric can lead to slightly different results. Users can now also supply their own scheme as long as it follows the signature of cellrank.tl.kernels.SimilaritySchemeABC.

  • cellrank.datasets.reprogramming() has been added to allow for easy reproducibility of the time & memory benchmarking results in our manuscript [Lange et al., 2022]. This is a reprogramming dataset from [Biddy et al., 2018].