(chore): generate 1.10.4 release notes

Author: flying-sheep

docs/release-notes/1.10.4.md

@@ -0,0 +1,34 @@
+(v1.10.4)=
+### 1.10.4 {small}`2024-11-12`
+
+### Breaking changes
+
+- Remove Python 3.9 support {smaller}`P Angerer` ({pr}`3283`)
+
+### Bug fixes
+
+- Fix {meth}`scanpy.pl.DotPlot.style`, {meth}`scanpy.pl.MatrixPlot.style`, and {meth}`scanpy.pl.StackedViolin.style` resetting all non-specified parameters {smaller}`P Angerer` ({pr}`3206`)
+- Accept `'group'` instead of `'obs'` for `standard_scale` parameter in {func}`~scanpy.pl.stacked_violin` {smaller}`P Angerer` ({pr}`3243`)
+- Use `density_norm` instead of of `scale` (cont. from {pr}`2844`) in {func}`~scanpy.pl.violin` and {func}`~scanpy.pl.stacked_violin` {smaller}`P Angerer` ({pr}`3244`)
+- Switched all compatibility adapters for positional parameters to {exc}`FutureWarning` {smaller}`P Angerer` ({pr}`3264`)
+- Catch `PerfectSeparationWarning` during {func}`~scanpy.pp.regress_out` {smaller}`J Wagner` ({pr}`3275`)
+- Fix {func}`scanpy.pp.highly_variable_genes` for batches of size 1 {smaller}`P Angerer` ({pr}`3286`)
+- Fix {func}`scanpy.pl.scatter`’s `color` parameter to take collections as advertised {smaller}`P Angerer` ({pr}`3299`)
+- Fix {func}`scanpy.pl.highest_expr_genes` when used with a categorical gene symbol column {smaller}`P Angerer` ({pr}`3302`)
+
+### Features
+
+- Add `layer` argument to {func}`scanpy.tl.score_genes` and {func}`scanpy.tl.score_genes_cell_cycle` {smaller}`L Zappia` ({pr}`2921`)
+- Prevent `raw` conflict with `layer` in {func}`~scanpy.tl.score_genes` {smaller}`S Dicks` ({pr}`3155`)
+- Add support for `median` as an aggregation function to the `Aggregation` class in `scanpy.get._aggregated.py`. This allows for median-based aggregation of data (e.g., pseudobulk), complementing existing methods like mean- and sum-based aggregation {smaller}`M Dehkordi (Farhad)` ({pr}`3180`)
+- Add `key_added` argument to {func}`~scanpy.pp.pca`, {func}`~scanpy.tl.tsne` and {func}`~scanpy.tl.umap` {smaller}`P Angerer` ({pr}`3184`)
+- Support running {func}`scanpy.pp.pca` on sparse Dask arrays with the `'covariance_eigh'` solver {smaller}`P Angerer` ({pr}`3263`)
+- Use upstreamed {class}`~sklearn.decomposition.PCA` implementation for {class}`~scipy.sparse.csr_array` and {class}`~scipy.sparse.csr_matrix` (see {ref}`sklearn:changes_1_4`) {smaller}`P Angerer` ({pr}`3267`)
+- Add explicit support to {func}`scanpy.pp.pca` for `svd_solver='covariance_eigh'` {smaller}`P Angerer` ({pr}`3296`)
+- Add support {class}`dask.array.Array` to {func}`scanpy.pp.calculate_qc_metrics` {smaller}`I Gold` ({pr}`3307`)
+- Support `layer` parameter in {func}`scanpy.pl.highest_expr_genes` {smaller}`P Angerer` ({pr}`3324`)
+- Run numba functions single-threaded when called from inside of a ThreadPool {smaller}`P Angerer` ({pr}`3335`)
+
+### Performance
+
+- * Speed up {func}`~scanpy.pp.regress_out` {smaller}`P Ashish, P Angerer & S Dicks` ({pr}`3284`)