Release Notes

Version 1.0

1.3.1 2021-04-09

Bugfixes

  • Fix estimator’s lineages color/names mismatch when reading from anndata.AnnData PR 556.

  • Remove heuristics used to determine which solver to use PR 558.

1.3.0 2021-03-29

This release includes some major additions which make CellRank more applicable with and without RNA velocity information. In particular, it includes:

Additions

Bugfixes

  • Fix various bugs when plotting multiple gene trends PR 487.

  • Fix gene trend smoothing not working for 1 lineage PR 512.

  • Fix pandas error when computing macrostates PR 513.

  • Remove malfunctioning Edit on GitHub from the documentation PR 538.

1.2.0 2021-02-02

This release includes:

Additions

  • Completely refactored the underlying code base of GPCCA and set it up as it’s own package called pyGPCCA with documentation and an example. Going forwards, this will ensure that one of the “engines” of CellRank is also easy to maintain to extend. Further, this will make CellRank’s installation more convenient by not needing to vendorize additional dependencies PR 472.

  • Add cellrank.pl.circular_projection() visualizing computed fate probabilities as done in [Velten et al., 2017], see Plot circular embedding. PR 459.

  • Allow legends not to be plotted by passing legend_loc="none", as done in scVelo PR 470.

Bugfixes

1.1.0 2020-11-17

This release includes:

Additions

  • 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 CellRank preprint. This is a reprogramming dataset from [Biddy et al., 2018].

Bugfixes

  • Fix not vendorizing correct msmtools which sometimes caused densification of a sparse matrix.

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

1.0.0 2020-10-17

1.0.0-rc.11 2020-09-25

1.0.0-rc.0 2020-07-15

1.0.0-b.8 2020-07-12

  • Add installation options for PETSc and SLEPc

  • Add iterative solver for absorption probabilities

  • Add minor cellrank.tl.Lineage improvements

  • Fix docstring issues

1.0.0-b.2 2020-07-02

  • Fix installation by including future-fstrings

1.0.0-b.1 2020-07-02

  • Initial beta pre-release