# Release Notes¶

## Version 0.2.5 Oct 14, 2022¶

Changes:

Catch non-positive parameter values and raise a ValueError if necessary (PR 614).

get_mean_var uses the same size parameter for mean and variance (PR 698).

Bugfixes:

filter_genes now works with adata.layers[‘unspliced’] being sparse and adata.layers[‘spliced’] dense (PR 537).

show_proportions actually considers the layer “ambiguous” if present (PR 587).

Fix calculation of Pearson’s correlation in csr_vcorrcoef (PR 679).

Fix get_mean_var to work with sparse input and ignore_zeros=True (PR 698).

Fix bug in neighbor calculation (PR 797).

Fix optimization.py::get_weight to work with numeric, non-integer values (PR 839).

Fix inference with fit_scaling=False (PR 848).

Fix saving of velocity embedding stream (PR 900).

Fix Pandas’ display precison when passed to get_df (PR 907).

## Version 0.2.4 Aug 26, 2021¶

Perspectives:

Landing page and two notebooks accompanying the perspectives manuscript at MSB.

New datasets: Gastrulation, bone marrow, and PBMCs.

New capabilities:

Added vignettes accompanying the NBT manuscript.

Kinetic simulations with time-dependent rates.

New arguments for tl.velocity_embedding_stream (PR 492).

Introduced automated code formatting flake8 and isort (PR 360, PR 374).

tl.velocity_graph parallelized (PR 392).

legend_align_text parameter in pl.scatter for smart placing of labels without overlapping.

Save option for pl.proportions.

Bugfixes:

Pinned sphinx<4.0 and nbsphinx<0.8.7.

Fix IPython import at CLI.

## Version 0.2.3 Feb 13, 2021¶

tl.recover_dynamics: Multicore implementation thanks to M Klein, Y Schaelte, P Weiler

CI now runs on GitHub Actions

New utility functions:

utils.gene_info: Retrieve gene information from biothings client.

utils.convert_to_ensembl and utils.convert_to_gene_names: Converting ensembl IDs into gene names and vice versa.

## Version 0.2.2 July 22, 2020¶

tl.paga: PAGA graph with velocity-directed edges.

Black code style

## Version 0.2.1 May 28, 2020¶

Bugfixes:

Correct identification of root cells in tl.latent_time thanks to M Lange

Correct usage of latent_time prior in tl.paga thanks to G Lubatti

## Version 0.2.0 May 12, 2020¶

New vignettes:

RNA velocity basics

Dynamical Modeling

Differential Kinetics

Tools:

tl.differential_kinetic_test: introduced a statistical test to detect different kinetic regimes.

tl.rank_dynamical_genes: introduced a gene ranking by cluster-wise likelihoods.

tl.paga: introduced directed PAGA graph

Plotting:

pl.scatter enhancements: linear and polynomical fits, gradient coloring

pl.proportions: Pie and bar chart of spliced/unspliced proprtions.

GridSpec: multiplot environment.

## Version 0.1.20 Sep 5, 2019¶

Tools:

tl.recover_dynamics: introduced a dynamical model inferring the full splicing kinetics, thereby identifying all kinetic rates of transcription, splicing and degradation.

tl.recover_latent_time: infers a shared latent time across all genes based on the learned splicing dynamics.

Plotting:

pl.scatter enhancements: multiplots, rugplot, linear and polynomial fits, density plots, etc.

pl.heatmap: heatmap / clustermap of genes along time coordinate sorted by expression along dynamics.

Preprocessing:

New attributes in pp.filter_genes: min_shared_counts and min_shared_genes.

Added fast neighbor search method: Hierarchical Navigable Small World graphs (HNSW)

## Version 0.1.14 Dec 7, 2018¶

Plotting:

New attriutes arrow_length and arrow_size for flexible adjustment of embedded velocities.

pl.velocity_graph: Scatter plot of embedding with cell-to-cell transition connectivities.

pl.velocity_embedding_stream: Streamplot visualization of velocities.

Improve visualization of embedded single cell velocities (autosize, colors etc.)

Tools:

tl.cell_fate: compute cell-specific terminal state likelihood

New attribute approx=True in tl.velocity_graph to enable approximate graph computation by performing cosine correlations on PCA space.

Preprocessing:

Automatically detect whether data is already preprocessed.

## Version 0.1.11 Oct 27, 2018¶

Plotting:

settings.set_figure_params(): adjust matplotlib defaults for beautified plots

improved default point and arrow sizes; improved quiver autoscale

enable direct plotting of

Tools:

tl.velocity_confidence: Added two confidence measures ‘velocity_confidence’ and ‘velocity_confidence_transition’.

tl.rank_velocity_genes: Added functionality to rank genes for velocity characterizing groups using a t-test.

New attribute perc in tl.velocity enables extreme quantile fit, e.g. set perc=95.

New attribute groups in tl.velocity enables velocity estimation only on a subset of the data.

Improved tl.transition_matrix by incorporating self-loops via self_transitions=True and state changes that have negative correlation with velocity (opposite direction) via use_negative_cosines=True

Utils:

utils.merge to merge to AnnData objects such as already existing AnnData and newly generated Loom File.

## Version 0.1.8 Sep 12, 2018¶

Plotting:

support saving plots as pdf, png etc.

support multiple colors and layers

quiver autoscaling for velocity plots

attributes added: figsize and dpi

Preprocessing:

filter_and_normalize() instead of recipe_velocity()

normalization of layers is done automatically when computing moments

Tools:

terminal_states: computes root and end points via eigenvalue decomposition thanks to M Lange

## Version 0.1.5 Sep 4, 2018¶

Support writing loom files

Support both dense and sparse layers

Plotting bugfixes

Added pp.recipe_velocity()

## Version 0.1.2 Aug 21, 2018¶

First alpha release of scvelo.