CellRank 1.3.0 (2021-03-29)¶
Bugfixes¶
Features¶
Add new kernel
cellrank.tl.kernels.CytoTRACEKernel
which computes cell-cell transition probabilities based on the CytoTRACE score [Gulati et al., 2020], a measure of differentiation potential, PR 527.Add external API
cellrank.external
with a stationary optimal transport kernelcellrank.external.kernels.OTKernel
contributed from [Zhang et al., 2021], as well as a contributing guide, PR 522.Rename
cellrank.tl.kernels.PalantirKernel
tocellrank.tl.kernels.PseudotimeKernel
and add hard threshold scheme inspired by [Setty et al., 2019], a soft threshold scheme inspired by [Stassen et al., 2021] and a custom scheme when computing the transition matrix, see e.g.cellrank.tl.kernels.SoftThresholdScheme
PR 514.Add more flexibility to
cellrank.tl.kernels.ConnectivityKernel
, allowing it to use any cell-cell similarities fromanndata.AnnData.obsp
, such as spatial similarities fromsquidpy
[Palla et al., 2021] PR 501.Add 2 new tutorials:
Beyond RNA velocity: shows how to use CellRank when no RNA velocity information is available. PR 32
Creating a new kernel: explains how to create your own custom kernel class that estimates cell-cell transition probabilities PR 31.
Add projection of transition matrix onto an embedding
cellrank.tl.kernels.Kernel.compute_projection()
Add random walk simulation and visualization in an embedding
cellrank.tl.kernels.Kernel.plot_random_walks()
PR 537.Add
cellrank.tl.Lineage.priming_degree()
PR 502 which estimates a cell’s plasticity/differentiation potential based on ideas by [Setty et al., 2019] and [Velten et al., 2017].Add checks for transition matrix irreducibility PR 516.
Add Zebrafish development dataset from [Farrell et al., 2018] PR 539.
Speed-up stationary distribution calculation in
pygpcca
PR 22.