feat: add illicofor rank_genes_groups

pyproject.toml

@@ -51,7 +51,7 @@ classifiers = [
 ]
 dynamic = [ "version" ]
 dependencies = [
-    "anndata>=0.10.8",
+    "anndata>=0.11",
     "certifi",
     "fast-array-utils[accel,sparse]>=1.4",
     "h5py>=3.11",
@@ -97,6 +97,7 @@ scanorama = [ "scanorama" ]
 scrublet = [ "scikit-image>=0.23.1" ]
 # highly_variable_genes method 'seurat_v3'
 skmisc = [ "scikit-misc>=0.5.1" ]
+illico = [ "illico>=0.5.1" ]
 scanpy2 = [ "igraph>=0.10.8", "scikit-misc>=0.5.1" ]
 
 [dependency-groups]
@@ -107,6 +108,7 @@ dev = [
 test = [
     "scanpy[dask-ml]",
     "scanpy[dask]",
+    "scanpy[illico]",
     "scanpy[leiden]",
     "scanpy[plotting]",
     "scanpy[scrublet]",

src/scanpy/_settings/presets.py

@@ -31,7 +31,9 @@
 ]
 
 
-type DETest = Literal["logreg", "t-test", "wilcoxon", "t-test_overestim_var"]
+type DETest = Literal[
+    "logreg", "t-test", "wilcoxon", "wilcoxon_illico", "t-test_overestim_var"
+]
 type HVGFlavor = Literal["seurat", "cell_ranger", "seurat_v3", "seurat_v3_paper"]
 type LeidenFlavor = Literal["leidenalg", "igraph"]
 

src/scanpy/tools/_rank_genes_groups.py

@@ -7,6 +7,7 @@
 import numba
 import numpy as np
 import pandas as pd
+from anndata import AnnData
 from fast_array_utils.numba import njit
 from fast_array_utils.stats import mean_var
 from scipy import sparse
@@ -28,7 +29,6 @@
     from collections.abc import Generator, Iterable
     from typing import Literal
 
-    from anndata import AnnData
     from numpy.typing import NDArray
 
 
@@ -141,6 +141,7 @@ def __init__(
             self.expm1_func = lambda x: np.expm1(x * np.log(base))
         else:
             self.expm1_func = np.expm1
+        self.group_col = adata.obs[groupby].array
 
         self.groups_order, self.groups_masks_obs = _utils.select_groups(
             adata, groups, groupby
@@ -424,7 +425,7 @@ def logreg(
             if len(self.groups_order) <= 2:
                 break
 
-    def compute_statistics(  # noqa: PLR0912
+    def compute_statistics(  # noqa: PLR0912, PLR0915
         self,
         method: DETest,
         *,
@@ -441,8 +442,63 @@ def compute_statistics(  # noqa: PLR0912
             if not mean_in_log_space:
                 # If we are not exponentiating after the mean aggregation, we need to recalculate the stats.
                 self._basic_stats(exponentiate_values=True)
-        elif method == "wilcoxon":
-            generate_test_results = self.wilcoxon(tie_correct=tie_correct)
+        elif "wilcoxon" in method:
+            if "illico" in method:
+                from illico import asymptotic_wilcoxon
+
+                illico_df = asymptotic_wilcoxon(
+                    AnnData(
+                        X=self.X,
+                        var=pd.DataFrame(index=self.var_names),
+                        obs=pd.DataFrame(
+                            index=pd.RangeIndex(self.X.shape[0]).astype("str"),
+                            # This self.group_col means illico will run tests against *all* data
+                            # instead of what's in self.groups_order as controlled by the `groups` arg.
+                            # TODO: Only run the subset once illico supports a `groups` argument
+                            data={"group": self.group_col},
+                        ),
+                    ),
+                    reference=self.groups_order[self.ireference]
+                    if self.ireference is not None
+                    else None,
+                    group_keys="group",
+                    return_as_scanpy=False,
+                    is_log1p=True,
+                    tie_correct=tie_correct,
+                    use_continuity=False,
+                    alternative="two-sided",
+                    use_rust=False,
+                )
+                # Generate a lookup of category -> result excluding the refernece if it is present.
+                generate_test_results_map = {
+                    group_cat: (
+                        group["z_score"].to_numpy(copy=True),
+                        group["p_value"].to_numpy(copy=True),
+                    )
+                    for (_, group) in illico_df.groupby(level="pert")
+                    if (
+                        group_cat := np.unique(
+                            group.index.get_level_values("pert").to_numpy(copy=True)
+                        ).item()
+                    )
+                    != (
+                        None
+                        if self.ireference is None
+                        else self.groups_order[self.ireference]
+                    )
+                }
+                # Create the iterator that is expected by the other method-branches.
+                groups_order_list = self.groups_order.tolist()
+                generate_test_results = (
+                    (
+                        groups_order_list.index(group_cat),
+                        *generate_test_results_map[group_cat],
+                    )
+                    for group_cat in self.groups_order
+                    if group_cat in generate_test_results_map
+                )
+            else:
+                generate_test_results = self.wilcoxon(tie_correct=tie_correct)
             # If we're not exponentiating after the mean aggregation, then do it now.
             self._basic_stats(exponentiate_values=not mean_in_log_space)
         elif method == "logreg":
@@ -451,7 +507,6 @@ def compute_statistics(  # noqa: PLR0912
         self.stats = None
 
         n_genes = self.X.shape[1]
-
         for group_index, scores, pvals in generate_test_results:
             group_name = str(self.groups_order[group_index])
 

src/testing/scanpy/_pytest/marks.py

@@ -41,6 +41,7 @@ def _generate_next_value_(
     skimage = "scikit-image"
     skmisc = "scikit-misc"
     zarr = auto()
+    illico = auto()
     # external
     bbknn = auto()
     harmony = "harmonyTS"

tests/test_rank_genes_groups.py

@@ -20,10 +20,11 @@
 from scanpy.tools._rank_genes_groups import _RankGenes
 from testing.scanpy._helpers import random_mask
 from testing.scanpy._helpers.data import pbmc68k_reduced
+from testing.scanpy._pytest.marks import needs
 from testing.scanpy._pytest.params import ARRAY_TYPES, ARRAY_TYPES_MEM
 
 if TYPE_CHECKING:
-    from collections.abc import Callable
+    from collections.abc import Callable, Sequence
     from typing import Any, Literal
 
     from numpy.lib.npyio import NpzFile
@@ -352,6 +353,79 @@ def test_mask_not_equal():
     assert not np.array_equal(no_mask, with_mask)
 
 
+@pytest.mark.parametrize("corr_method", ["benjamini-hochberg", "bonferroni"])
+@pytest.mark.parametrize("test", ["ovo", "ovr"])
+@pytest.mark.parametrize("exp_post_agg", [True, False], ids=["post_exp", "pre_exp"])
+@pytest.mark.parametrize(
+    "tie_correct", [True, False], ids=["tie_correct", "no_tie_correct"]
+)
+@pytest.mark.parametrize("groups", [["CD14+ Monocyte", "Dendritic"], "all"])
+@pytest.mark.filterwarnings("ignore:invalid value encountered:RuntimeWarning")
+@needs.illico
+def test_illico(
+    test: Literal["ovo", "ovr"],
+    corr_method: Literal["benjamini-hochberg", "bonferroni"],
+    subtests: pytest.Subtests,
+    groups: Literal["all"] | Sequence[str],
+    *,
+    exp_post_agg: bool,
+    tie_correct: bool,
+):
+
+    pbmc = pbmc68k_reduced()
+    pbmc.raw.X.sum_duplicates()
+    pbmc.raw.X.sort_indices()
+    pbmc_illico = pbmc.copy()
+
+    reference = pbmc.obs["bulk_labels"].iloc[0] if test == "ovo" else "rest"
+    sc.tl.rank_genes_groups(
+        pbmc_illico,
+        groupby="bulk_labels",
+        method="wilcoxon_illico",
+        reference=reference if test == "ovo" else "rest",
+        n_genes=pbmc.n_vars,
+        tie_correct=tie_correct,
+        corr_method=corr_method,
+        exp_post_agg=exp_post_agg,
+        groups=groups,
+    )
+
+    sc.tl.rank_genes_groups(
+        pbmc,
+        groupby="bulk_labels",
+        method="wilcoxon",
+        reference=reference if test == "ovo" else "rest",
+        n_genes=pbmc.n_vars,
+        tie_correct=tie_correct,
+        corr_method=corr_method,
+        exp_post_agg=exp_post_agg,
+        groups=groups,
+    )
+    scanpy_results = pbmc.uns["rank_genes_groups"]
+    illico_results = pbmc_illico.uns["rank_genes_groups"]
+    assert set(illico_results.keys()) == set(scanpy_results.keys()), (
+        "Output keys do not match Scanpy's output format."
+    )
+
+    for k, ref in scanpy_results.items():
+        with subtests.test(k):
+            if k in ["params", "names"]:
+                # We can skip names ordering check as if incorrect, other values will mismatch
+                continue
+            res = np.array(illico_results[k].tolist())
+            ref_arr = np.array(ref.tolist())
+            mask = np.isfinite(ref_arr) * np.isfinite(
+                res
+            )  # Mask to ignore inf values in the comparison
+            np.testing.assert_allclose(
+                ref_arr[mask],
+                res[mask],
+                rtol=0,
+                atol=1e-6,
+                err_msg=f"Mismatch in '{k}' values between asymptotic_wilcoxon and Scanpy outputs.",
+            )
+
+
 @pytest.mark.parametrize(
     ("mean_in_log_space", "expected_logfc"),
     [