1.10.0.md

(v1.10.0)=

1.10.0 {small}2024-03-26

scanpy 1.10 brings a large amount of new features, performance improvements, and improved documentation.

Some highlights:

• Improved support for out-of-core workflows via dask. See new tutorial: {doc}/tutorials/experimental/dask demonstrating counts-to-clusters for 1.4 million cells in <10 min.
• A new {doc}basic clustering tutorial </tutorials/basics/clustering> demonstrating an updated workflow.
• Opt-in increased performance for neighbor search and clustering ({doc}how to guide </how-to/knn-transformers>).
• Ability to mask observations or variables from a number of methods (see {doc}/tutorials/plotting/advanced for an example with plotting embeddings)
• A new function {func}~scanpy.get.aggregate for computing aggregations of your data, very useful for pseudo bulking!

Features

• {func}~scanpy.pp.scrublet and {func}~scanpy.pp.scrublet_simulate_doublets were moved from {mod}scanpy.external.pp to {mod}scanpy.pp. The scrublet implementation is now maintained as part of scanpy {pr}2703 {smaller}P Angerer
• {func}scanpy.pp.pca, {func}scanpy.pp.scale, {func}scanpy.pl.embedding, and {func}scanpy.experimental.pp.normalize_pearson_residuals_pca now support a mask parameter {pr}2272 {smaller}C Bright, T Marcella, & P Angerer
• Enhanced dask support for some internal utilities, paving the way for more extensive dask support {pr}2696 {smaller}P Angerer
• {func}scanpy.pp.highly_variable_genes supports dask for the default seurat and cell_ranger flavors {pr}2809 {smaller}P Angerer
• New function {func}scanpy.get.aggregate which allows grouped aggregations over your data. Useful for pseudobulking! {pr}2590 {smaller}Isaac Virshup {smaller}Ilan Gold {smaller}Jon Bloom
• {func}scanpy.pp.neighbors now has a transformer argument allowing the use of different ANN/ KNN libraries {pr}2536 {smaller}P Angerer
• {func}scanpy.experimental.pp.highly_variable_genes using flavor='pearson_residuals' now uses numba for variance computation and is faster {pr}2612 {smaller}S Dicks & P Angerer
• {func}scanpy.tl.leiden now offers igraph's implementation of the leiden algorithm via via flavor when set to igraph. leidenalg's implementation is still default, but discouraged. {pr}2815 {smaller}I Gold
• {func}scanpy.pp.highly_variable_genes has new flavor seurat_v3_paper that is in its implementation consistent with the paper description in Stuart et al 2018. {pr}2792 {smaller}E Roellin
• {func}scanpy.datasets.blobs now accepts a random_state argument {pr}2683 {smaller}E Roellin
• {func}scanpy.pp.pca and {func}scanpy.pp.regress_out now accept a layer argument {pr}2588 {smaller}S Dicks
• {func}scanpy.pp.subsample with copy=True can now be called in backed mode {pr}2624 {smaller}E Roellin
• {func}scanpy.pp.harmony_integrate now runs with 64 bit floats improving reproducibility {pr}2655 {smaller}S Dicks
• {func}scanpy.tl.rank_genes_groups no longer warns that it's default was changed from t-test_overestim_var to t-test {pr}2798 {smaller}L Heumos
• scanpy.pp.calculate_qc_metrics now allows qc_vars to be passed as a string {pr}2859 {smaller}N Teyssier
• {func}scanpy.tl.leiden and {func}scanpy.tl.louvain now store clustering parameters in the key provided by the key_added parameter instead of always writing to (or overwriting) a default key {pr}2864 {smaller}J Fan
• {func}scanpy.pp.scale now clips np.ndarray also at - max_value for zero-centering {pr}2913 {smaller}S Dicks
• Support sparse chunks in dask {func}~scanpy.pp.scale, {func}~scanpy.pp.normalize_total and {func}~scanpy.pp.highly_variable_genes (seurat and cell-ranger tested) {pr}2856 {smaller}ilan-gold

Documentation

• Doc style overhaul {pr}2220 {smaller}A Gayoso
• Re-add search-as-you-type, this time via readthedocs-sphinx-search {pr}2805 {smaller}P Angerer
• Fixed a lot of broken usage examples {pr}2605 {smaller}P Angerer
• Improved harmonization of return field of sc.pp and sc.tl functions {pr}2742 {smaller}E Roellin
• Improved docs for percent_top argument of {func}~scanpy.pp.calculate_qc_metrics {pr}2849 {smaller}I Virshup
• New basic clustering tutorial ({doc}/tutorials/basics/clustering), based on one from scverse-tutorials {pr}2901 {smaller}I Virshup
• Overhauled {doc}/tutorials/index page, and added new {doc}/how-to/index section to docs {pr}2901 {smaller}I Virshup
• Added a new tutorial on working with dask ({doc}/tutorials/experimental/dask) {pr}2901 {smaller}I Gold {smaller}I Virshup

Bug fixes

• Updated {func}~scanpy.read_visium such that it can read spaceranger 2.0 files {smaller}L Lehner
• Fix {func}~scanpy.pp.normalize_total for dask {pr}2466 {smaller}P Angerer
• Fix setting :attr:scanpy.settings.verbosity in some cases {pr}2605 {smaller}P Angerer
• Fix all remaining pandas warnings {pr}2789 {smaller}P Angerer
• Fix some annoying plotting warnings around violin plots {pr}2844 {smaller}P Angerer
• Scanpy now has a test job which tests against the minumum versions of the dependencies. In the process of implementing this, many bugs associated with using older versions of pandas, anndata, numpy, and matplotlib were fixed. {pr}2816 {smaller}I Virshup
• Fix warnings caused by internal usage of pandas.DataFrame.stack with pandas>=2.1 {pr}2864{smaller}I Virshup
• {func}scanpy.get.aggregate now always returns {class}numpy.ndarray {pr}2893 {smaller}S Dicks
• Removes self from array of neighbors for use_approx_neighbors = True in {func}~scanpy.pp.scrublet {pr}2896{smaller}S Dicks
• Compatibility with scipy 1.13 {pr}2943 {smaller}I Virshup
• Fix use of {func}~scanpy.tl.dendrogram on highly correlated low precision data {pr}2928 {smaller}P Angerer
• Fix pytest deprecation warning {pr}2879 {smaller}P Angerer

Development Process

• Scanpy is now tested against python 3.12 {pr}2863 {smaller}ivirshup
• Fix testing package build {pr}2468 {smaller}P Angerer

Deprecations

• Dropped support for Python 3.8. More details here. {pr}2695 {smaller}P Angerer
• Deprecated specifying large numbers of function parameters by position as opposed to by name/keyword in all public APIs. e.g. prefer sc.tl.umap(adata, min_dist=0.1, spread=0.8) over sc.tl.umap(adata, 0.1, 0.8) {pr}2702 {smaller}P Angerer
• Dropped support for umap<0.5 for performance reasons. {pr}2870 {smaller}P Angerer