CellRank 1.1.0 (2020-11-17)#
Fix not vendorizing correct
msmtoolswhich 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.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].