From 4d39b85120aae9740d5a19e8c436f5df663ec383 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 10:55:48 -0800
Subject: [PATCH 01/18] refactor: update to new pdex

---
 pyproject.toml              | 10 +++++++---
 src/cell_eval/_baseline.py  | 11 +++++------
 src/cell_eval/_evaluator.py | 38 +++++++++++--------------------------
 tests/test_eval.py          |  6 +++---
 4 files changed, 26 insertions(+), 39 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index b0f6ca1..2c5e5a1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,10 +8,10 @@ authors = [
     { name = "Abhinav Adduri", email = "abhinav.adduri@arcinstitute.org" },
     { name = "Yusuf Roohani", email = "yusuf.roohani@arcinstitute.org" },
 ]
-requires-python = ">=3.10,<3.13"
+requires-python = ">=3.11,<3.13"
 dependencies = [
     "igraph>=0.11.8",
-    "pdex>=0.1.26",
+    "pdex>=0.2.0",
     "polars>=1.30.0",
     "pyyaml>=6.0.2",
     "scanpy>=1.10.3",
@@ -24,7 +24,11 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [dependency-groups]
-dev = ["ipykernel>=6.29.5", "pytest>=8.3.5", "ruff>=0.11.8"]
+dev = [
+    "ipykernel>=6.29.5",
+    "pytest>=8.3.5",
+    "ruff>=0.11.8",
+]
 
 [project.scripts]
 cell-eval = "cell_eval.__main__:main"
diff --git a/src/cell_eval/_baseline.py b/src/cell_eval/_baseline.py
index 7ad1107..e92874b 100644
--- a/src/cell_eval/_baseline.py
+++ b/src/cell_eval/_baseline.py
@@ -5,7 +5,7 @@
 import numpy as np
 import polars as pl
 from numpy.typing import NDArray
-from pdex import parallel_differential_expression
+from pdex import pdex
 from scipy.sparse import issparse
 
 from ._evaluator import _build_pdex_kwargs, _convert_to_normlog
@@ -83,16 +83,15 @@ def build_base_mean_adata(
     if output_de_path is not None:
         logger.info("Calculating differential expression")
         pdex_kwargs = _build_pdex_kwargs(
-            groupby_key=pert_col,
+            groupby=pert_col,
             reference=control_pert,
-            num_workers=num_threads,
-            metric=de_method,
-            batch_size=batch_size,
+            threads=num_threads,
             allow_discrete=allow_discrete,
             pdex_kwargs=pdex_kwargs,
         )
-        frame = parallel_differential_expression(
+        frame = pdex(
             adata=baseline_adata,
+            mode="ref",
             **pdex_kwargs,
         )
         logger.info(f"Saving differential expression results to {output_de_path}")
diff --git a/src/cell_eval/_evaluator.py b/src/cell_eval/_evaluator.py
index 0e86ce8..f4cb0ab 100644
--- a/src/cell_eval/_evaluator.py
+++ b/src/cell_eval/_evaluator.py
@@ -7,7 +7,7 @@
 import pandas as pd
 import polars as pl
 import scanpy as sc
-from pdex import parallel_differential_expression
+from pdex import pdex
 
 from cell_eval.utils import guess_is_lognorm
 
@@ -233,9 +233,7 @@ def _build_de_comparison(
             mode="real",
             de_path=de_real,
             anndata_pair=anndata_pair,
-            de_method=de_method,
             num_threads=num_threads,
-            batch_size=batch_size,
             allow_discrete=allow_discrete,
             outdir=outdir,
             prefix=prefix,
@@ -245,9 +243,7 @@ def _build_de_comparison(
             mode="pred",
             de_path=de_pred,
             anndata_pair=anndata_pair,
-            de_method=de_method,
             num_threads=num_threads,
-            batch_size=batch_size,
             allow_discrete=allow_discrete,
             outdir=outdir,
             prefix=prefix,
@@ -258,32 +254,23 @@ def _build_de_comparison(
 
 def _build_pdex_kwargs(
     reference: str,
-    groupby_key: str,
-    num_workers: int,
-    batch_size: int,
-    metric: str,
+    groupby: str,
+    threads: int,
     allow_discrete: bool,
     pdex_kwargs: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
     pdex_kwargs = pdex_kwargs or {}
     if "reference" not in pdex_kwargs:
         pdex_kwargs["reference"] = reference
-    if "groupby_key" not in pdex_kwargs:
-        pdex_kwargs["groupby_key"] = groupby_key
-    if "num_workers" not in pdex_kwargs:
-        pdex_kwargs["num_workers"] = num_workers
-    if "batch_size" not in pdex_kwargs:
-        pdex_kwargs["batch_size"] = batch_size
-    if "metric" not in pdex_kwargs:
-        pdex_kwargs["metric"] = metric
+    if "groupby" not in pdex_kwargs:
+        pdex_kwargs["groupby"] = groupby
+    if "threads" not in pdex_kwargs:
+        pdex_kwargs["threads"] = threads
     if "is_log1p" not in pdex_kwargs:
         if allow_discrete:
             pdex_kwargs["is_log1p"] = False
         else:
             pdex_kwargs["is_log1p"] = True
-
-    # always return polars DataFrames
-    pdex_kwargs["as_polars"] = True
     return pdex_kwargs
 
 
@@ -291,9 +278,7 @@ def _load_or_build_de(
     mode: Literal["pred", "real"],
     de_path: pl.DataFrame | str | None = None,
     anndata_pair: PerturbationAnndataPair | None = None,
-    de_method: str = "wilcoxon",
     num_threads: int = 1,
-    batch_size: int = 100,
     outdir: str | None = None,
     prefix: str | None = None,
     allow_discrete: bool = False,
@@ -305,16 +290,15 @@ def _load_or_build_de(
         logger.info(f"Computing DE for {mode} data")
         pdex_kwargs = _build_pdex_kwargs(
             reference=anndata_pair.control_pert,
-            groupby_key=anndata_pair.pert_col,
-            num_workers=num_threads,
-            metric=de_method,
-            batch_size=batch_size,
+            groupby=anndata_pair.pert_col,
+            threads=num_threads,
             allow_discrete=allow_discrete,
             pdex_kwargs=pdex_kwargs or {},
         )
         logger.info(f"Using the following pdex kwargs: {pdex_kwargs}")
-        frame = parallel_differential_expression(
+        frame = pdex(
             adata=anndata_pair.real if mode == "real" else anndata_pair.pred,
+            mode="ref",
             **pdex_kwargs,
         )
         if outdir is not None:
diff --git a/tests/test_eval.py b/tests/test_eval.py
index 968a701..541929c 100644
--- a/tests/test_eval.py
+++ b/tests/test_eval.py
@@ -265,7 +265,7 @@ def test_eval_pdex_kwargs():
         control_pert="control",
         pert_col="perturbation",
         pdex_kwargs={
-            "exp_post_agg": True,
+            "geometric_mean": False,
         },
     )
     evaluator.compute(
@@ -282,8 +282,8 @@ def test_eval_pdex_kwargs_duplicated():
         control_pert="control",
         pert_col="perturbation",
         pdex_kwargs={
-            "exp_post_agg": True,
-            "num_workers": 4,
+            "geometric_mean": False,
+            "threads": 4,
         },
     )
     evaluator.compute(

From 13bfa6cebe5f8dee63b184c3f6753bac08ccd567 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:08:14 -0800
Subject: [PATCH 02/18] refactor: remove unused pdex arguments for batch_size
 and metric

---
 src/cell_eval/_baseline.py  |  2 --
 src/cell_eval/_cli/_run.py  | 16 ----------------
 src/cell_eval/_evaluator.py |  4 ----
 3 files changed, 22 deletions(-)

diff --git a/src/cell_eval/_baseline.py b/src/cell_eval/_baseline.py
index e92874b..122edec 100644
--- a/src/cell_eval/_baseline.py
+++ b/src/cell_eval/_baseline.py
@@ -23,9 +23,7 @@ def build_base_mean_adata(
     allow_discrete: bool = False,
     output_path: str | None = None,
     output_de_path: str | None = None,
-    batch_size: int = 1000,
     num_threads: int = 1,
-    de_method: str = "wilcoxon",
     pdex_kwargs: dict[str, Any] = {},
 ) -> ad.AnnData:
     if isinstance(adata, str):
diff --git a/src/cell_eval/_cli/_run.py b/src/cell_eval/_cli/_run.py
index d40f541..d166045 100644
--- a/src/cell_eval/_cli/_run.py
+++ b/src/cell_eval/_cli/_run.py
@@ -79,18 +79,6 @@ def parse_args_run(parser: ap.ArgumentParser):
         default=1,
         help="Number of threads to use for parallel processing [default: %(default)s]",
     )
-    parser.add_argument(
-        "--batch-size",
-        type=int,
-        default=100,
-        help="Batch size for parallel processing [default: %(default)s]",
-    )
-    parser.add_argument(
-        "--de-method",
-        type=str,
-        default="wilcoxon",
-        help="Method to use for differential expression analysis [default: %(default)s]",
-    )
     parser.add_argument(
         "--allow-discrete",
         action="store_true",
@@ -166,9 +154,7 @@ def run_evaluation(args: ap.Namespace):
                 de_real=args.de_real,
                 control_pert=args.control_pert,
                 pert_col=args.pert_col,
-                de_method=args.de_method,
                 num_threads=args.num_threads,
-                batch_size=args.batch_size,
                 outdir=args.outdir,
                 allow_discrete=args.allow_discrete,
                 prefix=ct,
@@ -189,9 +175,7 @@ def run_evaluation(args: ap.Namespace):
             de_real=args.de_real,
             control_pert=args.control_pert,
             pert_col=args.pert_col,
-            de_method=args.de_method,
             num_threads=args.num_threads,
-            batch_size=args.batch_size,
             outdir=args.outdir,
             allow_discrete=args.allow_discrete,
             skip_de=args.profile == "pds",
diff --git a/src/cell_eval/_evaluator.py b/src/cell_eval/_evaluator.py
index f4cb0ab..2494434 100644
--- a/src/cell_eval/_evaluator.py
+++ b/src/cell_eval/_evaluator.py
@@ -96,9 +96,7 @@ def __init__(
                 anndata_pair=self.anndata_pair,
                 de_pred=de_pred,
                 de_real=de_real,
-                de_method=de_method,
                 num_threads=num_threads if num_threads != -1 else mp.cpu_count(),
-                batch_size=batch_size,
                 allow_discrete=allow_discrete,
                 outdir=outdir,
                 prefix=prefix,
@@ -220,9 +218,7 @@ def _build_de_comparison(
     anndata_pair: PerturbationAnndataPair | None = None,
     de_pred: pl.DataFrame | str | None = None,
     de_real: pl.DataFrame | str | None = None,
-    de_method: str = "wilcoxon",
     num_threads: int = 1,
-    batch_size: int = 100,
     allow_discrete: bool = False,
     outdir: str | None = None,
     prefix: str | None = None,

From e27697085c6d5a7816fc0a2d3574e9ae579df7ff Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:11:51 -0800
Subject: [PATCH 03/18] fix: properly recase float16 to float32 at minimum

---
 src/cell_eval/_evaluator.py | 25 +++++++++++++++++++++++++
 1 file changed, 25 insertions(+)

diff --git a/src/cell_eval/_evaluator.py b/src/cell_eval/_evaluator.py
index 2494434..8aff393 100644
--- a/src/cell_eval/_evaluator.py
+++ b/src/cell_eval/_evaluator.py
@@ -168,6 +168,10 @@ def _build_anndata_pair(
         logger.info(f"Reading pred anndata from {pred}")
         pred = ad.read_h5ad(pred)
 
+    # Cast float16 to float32 since NUMBA (used by pdex) does not support float16
+    _cast_float16_to_float32(real, which="real")
+    _cast_float16_to_float32(pred, which="pred")
+
     # Validate that the input is normalized and log-transformed
     _convert_to_normlog(real, which="real", allow_discrete=allow_discrete)
     _convert_to_normlog(pred, which="pred", allow_discrete=allow_discrete)
@@ -178,6 +182,27 @@ def _build_anndata_pair(
     )
 
 
+def _cast_float16_to_float32(adata: ad.AnnData, which: str | None = None):
+    """Cast float16 expression matrix to float32 (inplace).
+
+    NUMBA (used by pdex) does not support float16 operations.
+    """
+    import numpy as np
+    import scipy.sparse as sp
+
+    x = adata.X
+    dtype = x.dtype if not sp.issparse(x) else x.data.dtype
+    if dtype == np.float16:
+        if which:
+            logger.info(
+                f"Casting {which} anndata from float16 to float32 (NUMBA does not support float16)."
+            )
+        if sp.issparse(x):
+            adata.X = x.astype(np.float32)
+        else:
+            adata.X = x.astype(np.float32)
+
+
 def _convert_to_normlog(
     adata: ad.AnnData,
     which: str | None = None,

From e5407e42a84ef17fd106d0c2eeb95fba1e9a50f2 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:13:16 -0800
Subject: [PATCH 04/18] refactor: move recast to utils

---
 src/cell_eval/_evaluator.py | 22 +---------------------
 src/cell_eval/utils.py      | 20 ++++++++++++++++++++
 2 files changed, 21 insertions(+), 21 deletions(-)

diff --git a/src/cell_eval/_evaluator.py b/src/cell_eval/_evaluator.py
index 8aff393..a6cc767 100644
--- a/src/cell_eval/_evaluator.py
+++ b/src/cell_eval/_evaluator.py
@@ -13,6 +13,7 @@
 
 from ._pipeline import MetricPipeline
 from ._types import PerturbationAnndataPair, initialize_de_comparison
+from .utils import _cast_float16_to_float32
 
 logger = logging.getLogger(__name__)
 
@@ -182,27 +183,6 @@ def _build_anndata_pair(
     )
 
 
-def _cast_float16_to_float32(adata: ad.AnnData, which: str | None = None):
-    """Cast float16 expression matrix to float32 (inplace).
-
-    NUMBA (used by pdex) does not support float16 operations.
-    """
-    import numpy as np
-    import scipy.sparse as sp
-
-    x = adata.X
-    dtype = x.dtype if not sp.issparse(x) else x.data.dtype
-    if dtype == np.float16:
-        if which:
-            logger.info(
-                f"Casting {which} anndata from float16 to float32 (NUMBA does not support float16)."
-            )
-        if sp.issparse(x):
-            adata.X = x.astype(np.float32)
-        else:
-            adata.X = x.astype(np.float32)
-
-
 def _convert_to_normlog(
     adata: ad.AnnData,
     which: str | None = None,
diff --git a/src/cell_eval/utils.py b/src/cell_eval/utils.py
index f3f5ad1..4c6fbb9 100644
--- a/src/cell_eval/utils.py
+++ b/src/cell_eval/utils.py
@@ -2,6 +2,7 @@
 
 import anndata as ad
 import numpy as np
+import scipy.sparse as sp
 from scipy.sparse import csc_matrix, csr_matrix
 
 logger = logging.getLogger(__name__)
@@ -105,3 +106,22 @@ def split_anndata_on_celltype(
         ct: adata[adata.obs[celltype_col] == ct]
         for ct in adata.obs[celltype_col].unique()
     }
+
+
+def _cast_float16_to_float32(adata: ad.AnnData, which: str | None = None):
+    """Cast float16 expression matrix to float32 (inplace).
+
+    NUMBA (used by pdex) does not support float16 operations.
+    """
+
+    x = adata.X
+    dtype = x.dtype if not sp.issparse(x) else x.data.dtype
+    if dtype == np.float16:
+        if which:
+            logger.info(
+                f"Casting {which} anndata from float16 to float32 (NUMBA does not support float16)."
+            )
+        if sp.issparse(x):
+            adata.X = x.astype(np.float32)
+        else:
+            adata.X = x.astype(np.float32)

From f3ea3abead4e3ad0e68de16339e9fa953cde9030 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:14:51 -0800
Subject: [PATCH 05/18] test: remove unused alt metric

---
 tests/test_eval.py | 17 -----------------
 1 file changed, 17 deletions(-)

diff --git a/tests/test_eval.py b/tests/test_eval.py
index 541929c..79ee17a 100644
--- a/tests/test_eval.py
+++ b/tests/test_eval.py
@@ -390,20 +390,3 @@ def test_eval_downsampled_cells():
         break_on_error=True,
     )
     validate_expected_files(OUTDIR)
-
-
-def test_eval_alt_metric():
-    adata_real = build_random_anndata()
-    adata_pred = downsample_cells(adata_real, fraction=0.5)
-    evaluator = MetricsEvaluator(
-        adata_pred=adata_pred,
-        adata_real=adata_real,
-        control_pert=CONTROL_VAR,
-        pert_col=PERT_COL,
-        outdir=OUTDIR,
-        de_method="anderson",
-    )
-    evaluator.compute(
-        break_on_error=True,
-    )
-    validate_expected_files(OUTDIR)

From 824e63aa22b87870baea864bfdaa0e226c707d5f Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:15:03 -0800
Subject: [PATCH 06/18] chore: finish removing all outdated pdex arguments

---
 src/cell_eval/_evaluator.py | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/src/cell_eval/_evaluator.py b/src/cell_eval/_evaluator.py
index a6cc767..30e4dd1 100644
--- a/src/cell_eval/_evaluator.py
+++ b/src/cell_eval/_evaluator.py
@@ -39,12 +39,8 @@ class MetricsEvaluator:
         Control perturbation name.
     pert_col: str = "target"
         Perturbation column name.
-    de_method: str = "wilcoxon"
-        Differential expression method.
     num_threads: int = -1
         Number of threads for parallel differential expression.
-    batch_size: int = 100
-        Batch size for parallel differential expression.
     outdir: str = "./cell-eval-outdir"
         Output directory.
     allow_discrete: bool = False
@@ -64,9 +60,7 @@ def __init__(
         de_real: pl.DataFrame | str | None = None,
         control_pert: str = "non-targeting",
         pert_col: str = "target",
-        de_method: str = "wilcoxon",
         num_threads: int = -1,
-        batch_size: int = 100,
         outdir: str = "./cell-eval-outdir",
         allow_discrete: bool = False,
         prefix: str | None = None,

From 76b3f934e8c99ca0d49ffc8d0e4d2ce2d0a1429c Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:19:01 -0800
Subject: [PATCH 07/18] dep: added ty to project

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index 2c5e5a1..c776b55 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -28,6 +28,7 @@ dev = [
     "ipykernel>=6.29.5",
     "pytest>=8.3.5",
     "ruff>=0.11.8",
+    "ty>=0.0.19",
 ]
 
 [project.scripts]

From e25e1e1285640ce8148e30d2f3ae003f490aab70 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:27:31 -0800
Subject: [PATCH 08/18] style: fix all typing errors or ambiguities

---
 src/cell_eval/_baseline.py        | 13 ++++++------
 src/cell_eval/_cli/_prep.py       | 11 ++++++-----
 src/cell_eval/_types/_anndata.py  | 15 +++++++++-----
 src/cell_eval/metrics/_anndata.py | 30 +++++++++++++++++-----------
 src/cell_eval/metrics/base.py     |  4 ++--
 src/cell_eval/utils.py            | 16 +++++++++------
 tests/test_eval.py                | 13 ++++++------
 tutorials/vcc/vcc.ipynb           | 33 +++++--------------------------
 8 files changed, 66 insertions(+), 69 deletions(-)

diff --git a/src/cell_eval/_baseline.py b/src/cell_eval/_baseline.py
index 122edec..0ad610d 100644
--- a/src/cell_eval/_baseline.py
+++ b/src/cell_eval/_baseline.py
@@ -1,8 +1,9 @@
 import logging
-from typing import Any
+from typing import Any, cast
 
 import anndata as ad
 import numpy as np
+import pandas as pd
 import polars as pl
 from numpy.typing import NDArray
 from pdex import pdex
@@ -65,7 +66,7 @@ def build_base_mean_adata(
             (int(counts[counts_col].sum()), baseline.size),
             baseline,
         ),
-        var=adata.var,
+        var=cast(pd.DataFrame, adata.var),
         obs=obs,
     )
 
@@ -76,7 +77,7 @@ def build_base_mean_adata(
 
     if output_path is not None:
         logger.info(f"Saving baseline data to {output_path}")
-        baseline_adata.write_h5ad(output_path)
+        baseline_adata.write_h5ad(output_path)  # type: ignore[invalid-argument-type]
 
     if output_de_path is not None:
         logger.info("Calculating differential expression")
@@ -134,9 +135,9 @@ def _build_counts_df_from_adata(
         raise ValueError(
             f"Column '{pert_col}' not found in adata.obs: {adata.obs.columns}"
         )
-    if control_pert not in adata.obs[pert_col].unique():
+    if control_pert not in cast(pd.Series, adata.obs[pert_col]).unique():
         raise ValueError(
-            f"Control pert '{control_pert}' not found in adata.obs[{pert_col}]: {adata.obs[pert_col].unique()}"
+            f"Control pert '{control_pert}' not found in adata.obs[{pert_col}]: {cast(pd.Series, adata.obs[pert_col]).unique()}"
         )
     logger.info("Building counts DataFrame from adata")
     return (
@@ -158,7 +159,7 @@ def _build_pert_baseline(
         raise ValueError(
             f"Column '{pert_col}' not found in adata.obs: {adata.obs.columns}"
         )
-    unique_perts = adata.obs[pert_col].unique()
+    unique_perts = cast(pd.Series, adata.obs[pert_col]).unique()
     if control_pert not in unique_perts:
         raise ValueError(
             f"Control pert '{control_pert}' not found in unique_perts: {unique_perts}"
diff --git a/src/cell_eval/_cli/_prep.py b/src/cell_eval/_cli/_prep.py
index aba2e98..80e5d67 100644
--- a/src/cell_eval/_cli/_prep.py
+++ b/src/cell_eval/_cli/_prep.py
@@ -5,6 +5,7 @@
 import shutil
 import subprocess
 from tempfile import TemporaryDirectory
+from typing import cast
 
 import anndata as ad
 import numpy as np
@@ -136,9 +137,9 @@ def strip_anndata(
             raise ValueError(
                 f"Provided celltype column: '{celltype_col}' missing from anndata: {adata.obs.columns}"
             )
-    if ntc_name not in adata.obs[pert_col].unique():
+    if ntc_name not in cast(pd.Series, adata.obs[pert_col]).unique():
         raise ValueError(
-            f"Provided negative control name: '{ntc_name}' missing from anndata: {adata.obs[pert_col].unique()}"
+            f"Provided negative control name: '{ntc_name}' missing from anndata: {cast(pd.Series, adata.obs[pert_col]).unique()}"
         )
 
     # Check if expected dimension is provided and matches the length of the genelist
@@ -196,11 +197,11 @@ def strip_anndata(
 
     logger.info("Simplifying obs dataframe")
     new_obs = pd.DataFrame(
-        {output_pert_col: adata.obs[pert_col].values},
+        {output_pert_col: cast(pd.Series, adata.obs[pert_col]).values},
         index=np.arange(adata.shape[0]).astype(str),
     )
     if celltype_col:
-        new_obs[output_celltype_col] = adata.obs[celltype_col].values
+        new_obs[output_celltype_col] = cast(pd.Series, adata.obs[celltype_col]).values
 
     logger.info("Simplifying var dataframe")
     new_var = pd.DataFrame(
@@ -225,7 +226,7 @@ def strip_anndata(
 
         # Write the h5ad file
         logger.info(f"Writing h5ad output to {tmp_h5ad}")
-        minimal.write_h5ad(tmp_h5ad)
+        minimal.write_h5ad(tmp_h5ad)  # type: ignore[invalid-argument-type]
 
         # Zstd compress the h5ad file (will create pred.h5ad.zst)
         logger.info(f"Zstd compressing {tmp_h5ad}")
diff --git a/src/cell_eval/_types/_anndata.py b/src/cell_eval/_types/_anndata.py
index 2364ae1..3459d2e 100644
--- a/src/cell_eval/_types/_anndata.py
+++ b/src/cell_eval/_types/_anndata.py
@@ -1,9 +1,10 @@
 import logging
 from dataclasses import dataclass, field
-from typing import Iterator, Literal
+from typing import Iterator, Literal, cast
 
 import anndata as ad
 import numpy as np
+import pandas as pd
 import polars as pl
 from numpy.typing import NDArray
 from scipy.sparse import issparse
@@ -70,8 +71,12 @@ def __post_init__(self) -> None:
                 f"Perturbation column ({self.pert_col}) not found in pred AnnData: {self.pred.obs.columns}"
             )
 
-        perts_real = np.unique(self.real.obs[self.pert_col].to_numpy(str))
-        perts_pred = np.unique(self.pred.obs[self.pert_col].to_numpy(str))
+        perts_real = np.unique(
+            cast(pd.Series, self.real.obs[self.pert_col]).to_numpy(str)
+        )
+        perts_pred = np.unique(
+            cast(pd.Series, self.pred.obs[self.pert_col]).to_numpy(str)
+        )
         if not np.array_equal(perts_real, perts_pred):
             raise ValueError(
                 f"Perturbation mismatch: real {perts_real} != pred {perts_pred}"
@@ -90,10 +95,10 @@ def __post_init__(self) -> None:
         perts = np.array([p for p in perts if p != self.control_pert])
 
         pert_mask_real = self.pert_mask(
-            self.real.obs[self.pert_col].to_numpy(str),
+            cast(pd.Series, self.real.obs[self.pert_col]).to_numpy(str),
         )
         pert_mask_pred = self.pert_mask(
-            self.pred.obs[self.pert_col].to_numpy(str),
+            cast(pd.Series, self.pred.obs[self.pert_col]).to_numpy(str),
         )
 
         object.__setattr__(self, "perts", perts)
diff --git a/src/cell_eval/metrics/_anndata.py b/src/cell_eval/metrics/_anndata.py
index 8bcdf7d..458de62 100644
--- a/src/cell_eval/metrics/_anndata.py
+++ b/src/cell_eval/metrics/_anndata.py
@@ -1,7 +1,7 @@
 """Array metrics module."""
 
 from logging import getLogger
-from typing import Callable, Literal, Sequence
+from typing import Callable, Literal, Sequence, cast
 
 import anndata as ad
 import numpy as np
@@ -27,7 +27,7 @@ def pearson_delta(
     """Compute Pearson correlation between mean differences from control."""
     return _generic_evaluation(
         data,
-        pearsonr,  # type: ignore
+        pearsonr,
         use_delta=True,
         embed_key=embed_key,
     )
@@ -287,21 +287,21 @@ def _centroid_ann(
         feats = adata.obsm.get(embed_key, adata.X)  # type: ignore
 
         # Convert to float if not already
-        if feats.dtype != np.dtype("float64"):  # type: ignore
-            feats = feats.astype(np.float64)  # type: ignore
+        if feats.dtype != np.dtype("float64"):
+            feats = feats.astype(np.float64)
 
         # Densify if required
         if issparse(feats):
-            feats = feats.toarray()  # type: ignore
+            feats = feats.toarray()
 
-        cats = adata.obs[category_key].values
-        uniq, inv = np.unique(cats, return_inverse=True)  # type: ignore
-        centroids = np.zeros((uniq.size, feats.shape[1]), dtype=feats.dtype)  # type: ignore
+        cats = cast(pd.Series, adata.obs[category_key]).values
+        uniq, inv = np.unique(cats, return_inverse=True)
+        centroids = np.zeros((uniq.size, feats.shape[1]), dtype=feats.dtype)
 
         for i, cat in enumerate(uniq):
             mask = cats == cat
             if np.any(mask):
-                centroids[i] = feats[mask].mean(axis=0)  # type: ignore
+                centroids[i] = feats[mask].mean(axis=0)
 
         adc = ad.AnnData(X=centroids)
         adc.obs[category_key] = uniq
@@ -329,12 +329,20 @@ def __call__(self, data: PerturbationAnndataPair) -> float:
         self._cluster_leiden(
             ad_real_cent, self.real_resolution, real_key, self.n_neighbors
         )
-        ad_real_cent.obs = ad_real_cent.obs.set_index(data.pert_col).loc[cats_sorted]
+        ad_real_cent.obs = (
+            cast(pd.DataFrame, ad_real_cent.obs)
+            .set_index(data.pert_col)
+            .loc[cats_sorted]
+        )
         real_labels = pd.Categorical(ad_real_cent.obs[real_key])
 
         # 4. sweep predicted resolutions
         best_score = 0.0
-        ad_pred_cent.obs = ad_pred_cent.obs.set_index(data.pert_col).loc[cats_sorted]
+        ad_pred_cent.obs = (
+            cast(pd.DataFrame, ad_pred_cent.obs)
+            .set_index(data.pert_col)
+            .loc[cats_sorted]
+        )
         for r in self.pred_resolutions:
             pred_key = f"pred_clusters_{r}"
             self._cluster_leiden(ad_pred_cent, r, pred_key, self.n_neighbors)
diff --git a/src/cell_eval/metrics/base.py b/src/cell_eval/metrics/base.py
index e8e77c8..85a5a7b 100644
--- a/src/cell_eval/metrics/base.py
+++ b/src/cell_eval/metrics/base.py
@@ -22,10 +22,10 @@ class MetricResult:
     value: float | str
     perturbation: str | None = None
 
-    def to_dict(self) -> dict[str, float | str]:
+    def to_dict(self) -> dict[str, float | str | None]:
         """Convert result to dictionary."""
         return {
-            "perturbation": self.perturbation,  # type: ignore
+            "perturbation": self.perturbation,
             "metric": self.name,
             "value": self.value,
         }
diff --git a/src/cell_eval/utils.py b/src/cell_eval/utils.py
index 4c6fbb9..2b9f431 100644
--- a/src/cell_eval/utils.py
+++ b/src/cell_eval/utils.py
@@ -1,7 +1,9 @@
 import logging
+from typing import cast
 
 import anndata as ad
 import numpy as np
+import pandas as pd
 import scipy.sparse as sp
 from scipy.sparse import csc_matrix, csr_matrix
 
@@ -39,7 +41,7 @@ def guess_is_lognorm(
     if isinstance(adata.X, csr_matrix) or isinstance(adata.X, csc_matrix):
         frac, _ = np.modf(adata.X.data)
     elif adata.isview:
-        frac, _ = np.modf(adata.X.toarray())
+        frac, _ = np.modf(adata.X.toarray())  # type: ignore[unresolved-attribute]
     elif adata.X is None:
         raise ValueError("adata.X is None")
     else:
@@ -58,8 +60,8 @@ def guess_is_lognorm(
         max_val = adata.X.max()
         min_val = adata.X.min()
     else:
-        max_val = float(np.max(adata.X))
-        min_val = float(np.min(adata.X))
+        max_val = float(np.max(adata.X))  # type: ignore[no-matching-overload]
+        min_val = float(np.min(adata.X))  # type: ignore[no-matching-overload]
 
     # Validate range
     if min_val < 0:
@@ -104,7 +106,7 @@ def split_anndata_on_celltype(
 
     return {
         ct: adata[adata.obs[celltype_col] == ct]
-        for ct in adata.obs[celltype_col].unique()
+        for ct in cast(pd.Series, adata.obs[celltype_col]).unique()
     }
 
 
@@ -114,8 +116,10 @@ def _cast_float16_to_float32(adata: ad.AnnData, which: str | None = None):
     NUMBA (used by pdex) does not support float16 operations.
     """
 
-    x = adata.X
-    dtype = x.dtype if not sp.issparse(x) else x.data.dtype
+    x = cast(np.ndarray | csr_matrix | csc_matrix, adata.X)
+    dtype = (
+        x.dtype if not sp.issparse(x) else cast(csr_matrix | csc_matrix, x).data.dtype
+    )
     if dtype == np.float16:
         if which:
             logger.info(
diff --git a/tests/test_eval.py b/tests/test_eval.py
index 79ee17a..48beb4f 100644
--- a/tests/test_eval.py
+++ b/tests/test_eval.py
@@ -1,8 +1,9 @@
 import os
 import shutil
-from typing import Literal
+from typing import Literal, cast
 
 import numpy as np
+import pandas as pd
 import pytest
 
 from cell_eval import MetricsEvaluator
@@ -118,7 +119,7 @@ def test_broken_adata_missing_pertcol_in_real():
     adata_pred = adata_real.copy()
 
     # Remove pert_col from adata_real
-    adata_real.obs.drop(columns=[PERT_COL], inplace=True)
+    cast(pd.DataFrame, adata_real.obs).drop(columns=[PERT_COL], inplace=True)
 
     with pytest.raises(Exception):
         MetricsEvaluator(
@@ -135,7 +136,7 @@ def test_broken_adata_missing_pertcol_in_pred():
     adata_pred = adata_real.copy()
 
     # Remove pert_col from adata_pred
-    adata_pred.obs.drop(columns=[PERT_COL], inplace=True)
+    cast(pd.DataFrame, adata_pred.obs).drop(columns=[PERT_COL], inplace=True)
 
     with pytest.raises(Exception):
         MetricsEvaluator(
@@ -195,7 +196,7 @@ def test_unknown_alternative_de_metric():
             control_pert=CONTROL_VAR,
             pert_col=PERT_COL,
             outdir=OUTDIR,
-            de_method="unknown",
+            de_method="unknown",  # type: ignore[unknown-argument]
         ).compute()
 
 
@@ -239,8 +240,8 @@ def test_eval_missing_celltype_col():
     adata_real = build_random_anndata()
     adata_pred = downsample_cells(adata_real, fraction=0.5)
 
-    adata_real.obs.drop(columns="celltype", inplace=True)
-    adata_pred.obs.drop(columns="celltype", inplace=True)
+    cast(pd.DataFrame, adata_real.obs).drop(columns="celltype", inplace=True)
+    cast(pd.DataFrame, adata_pred.obs).drop(columns="celltype", inplace=True)
 
     assert "celltype" not in adata_real.obs.columns
     assert "celltype" not in adata_pred.obs.columns
diff --git a/tutorials/vcc/vcc.ipynb b/tutorials/vcc/vcc.ipynb
index 5f023c2..e2dc17f 100644
--- a/tutorials/vcc/vcc.ipynb
+++ b/tutorials/vcc/vcc.ipynb
@@ -239,32 +239,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "3879267c",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# Define our path to the training anndata\n",
-    "tr_adata_path = \"./adata_Training.h5ad\"\n",
-    "\n",
-    "# Read in the anndata\n",
-    "tr_adata = ad.read_h5ad(tr_adata_path)\n",
-    "\n",
-    "# Filter for non-targeting\n",
-    "ntc_adata = tr_adata[tr_adata.obs[\"target_gene\"] == \"non-targeting\"]\n",
-    "\n",
-    "# Append the non-targeting controls to the example anndata if they're missing\n",
-    "if \"non-targeting\" not in adata.obs[\"target_gene\"].unique():\n",
-    "    assert np.all(adata.var_names.values == ntc_adata.var_names.values), (\n",
-    "        \"Gene-Names are out of order or unequal\"\n",
-    "    )\n",
-    "    adata = ad.concat(\n",
-    "        [\n",
-    "            adata,\n",
-    "            ntc_adata,\n",
-    "        ]\n",
-    "    )"
-   ]
+   "source": "import pandas as pd\n\n# Define our path to the training anndata\ntr_adata_path = \"./adata_Training.h5ad\"\n\n# Read in the anndata\ntr_adata = ad.read_h5ad(tr_adata_path)\n\n# Filter for non-targeting\nntc_adata = tr_adata[tr_adata.obs[\"target_gene\"] == \"non-targeting\"]\n\n# Append the non-targeting controls to the example anndata if they're missing\nif \"non-targeting\" not in pd.Series(adata.obs[\"target_gene\"]).unique():\n    assert np.array_equal(adata.var_names, ntc_adata.var_names), (\n        \"Gene-Names are out of order or unequal\"\n    )\n    adata = ad.concat(\n        [\n            adata,\n            ntc_adata,\n        ]\n    )"
   },
   {
    "cell_type": "markdown",
@@ -276,13 +255,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "386ee994",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "adata.write_h5ad(\"./example.h5ad\")"
-   ]
+   "source": "adata.write_h5ad(\"./example.h5ad\")  # type: ignore[invalid-argument-type]"
   },
   {
    "cell_type": "markdown",
@@ -336,4 +313,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file

From 4c529f9fa9f99caf3269aaa9abfa75eee0ab15ae Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:28:42 -0800
Subject: [PATCH 09/18] ci: added typing to ci

---
 .github/workflows/CI.yml | 25 ++++++++++++++++++++++++-
 1 file changed, 24 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index 105b8cc..ffa890d 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -5,7 +5,7 @@ on: [push, pull_request]
 jobs:
   all_jobs:
     runs-on: ubuntu-latest
-    needs: [formatting, pytest, cli-test]
+    needs: [formatting, typing, pytest, cli-test]
     steps:
       - name: Complete
         run: echo "Complete"
@@ -50,6 +50,29 @@ jobs:
         run: |
           uv run ruff format --check
 
+  typing:
+    runs-on: ubuntu-latest
+
+    needs: [install-job]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+          cache-dependency-glob: "pyproject.toml"
+          python-version: "3.12"
+
+      - name: install dependencies
+        run: |
+          uv sync --all-extras --dev
+
+      - name: run type checking
+        run: |
+          uv run ty check
+
   pytest:
     runs-on: ubuntu-latest
 

From a3609d14097555bd521e20fe23b50df24371f38a Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:36:16 -0800
Subject: [PATCH 10/18] chore: remove unused configuration

---
 pyproject.toml | 4 ----
 ruff.toml      | 5 -----
 2 files changed, 9 deletions(-)
 delete mode 100644 ruff.toml

diff --git a/pyproject.toml b/pyproject.toml
index c776b55..d1bba78 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,7 +33,3 @@ dev = [
 
 [project.scripts]
 cell-eval = "cell_eval.__main__:main"
-
-[tool.pyright]
-venvPath = "."
-venv = ".venv"
diff --git a/ruff.toml b/ruff.toml
deleted file mode 100644
index 235fc08..0000000
--- a/ruff.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[lint]
-select = ["E", "F", "ERA"]
-
-[lint.pycodestyle]
-max-line-length = 120

From fe81c31c6b91e84034fa267c1719efdae029c641 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:36:22 -0800
Subject: [PATCH 11/18] feat: added a claude md

---
 CLAUDE.md | 84 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 84 insertions(+)
 create mode 100644 CLAUDE.md

diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 100644
index 0000000..cda10e2
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1,84 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+**cell-eval** is a Python package and CLI tool for evaluating the performance of models that predict cellular responses to perturbations at the single-cell level. Developed by the Arc Research Institute.
+
+It generally revolves around a *real* anndata and a *predicted* anndata where it measures the general differences between the two across a variety of metrics.
+
+- Python 3.11–3.12, managed with **UV** and built with **hatchling**
+- CLI entry point: `cell-eval` (defined in `src/cell_eval/__main__.py`)
+
+## Common Commands
+
+```bash
+# Install dependencies
+uv sync --all-extras --dev
+
+# Run all tests
+uv run pytest -v
+
+# Run a single test
+uv run pytest tests/test_eval.py::test_broken_adata_not_normlog -v
+
+# Formatting (check / fix)
+uv run ruff format --check
+uv run ruff format
+
+# Type checking
+uv run ty check
+
+# Verify CLI works
+uv run cell-eval --help
+```
+
+CI runs: formatting, typing, pytest, and cli-test (see `.github/workflows/CI.yml`).
+
+## Architecture
+
+### Core Data Flow
+
+```
+AnnData inputs (predicted + real)
+  → MetricsEvaluator (validation, normalization, DE computation)
+    → MetricPipeline (profile-based metric selection + execution)
+      → metrics_registry (global MetricRegistry instance)
+        → individual metric functions
+  → polars DataFrames (per-perturbation + aggregated results)
+```
+
+### Key Abstractions
+
+- **`MetricsEvaluator`** (`src/cell_eval/_evaluator.py`) — Main programmatic entry point. Validates input AnnData objects, computes differential expression via `pdex`, and orchestrates the metric pipeline.
+
+- **`MetricRegistry`** (`src/cell_eval/metrics/_registry.py`) — Global singleton `metrics_registry`. Metrics are registered with a name, type (`DE` or `ANNDATA_PAIR`), compute function, and best-value indicator. Supports both plain functions and class-based metrics requiring instantiation.
+
+- **`MetricPipeline`** (`src/cell_eval/_pipeline/_runner.py`) — Selects and runs metrics based on a profile (`full`, `minimal`, `vcc`, `de`, `anndata`, `pds`). Collects per-perturbation results and aggregates them.
+
+- **`Metric` protocol** (`src/cell_eval/metrics/base.py`) — All metric functions take either a `PerturbationAnndataPair` or `DEComparison` and return `float | dict[str, float]`.
+
+- **Type system** (`src/cell_eval/_types/`) — Immutable dataclasses: `PerturbationAnndataPair`, `DEComparison`, plus enums `MetricType`, `MetricBestValue`, `DESortBy`.
+
+### Metrics
+
+Metrics are split into two categories registered in `src/cell_eval/metrics/_impl.py`:
+
+- **AnnData metrics** (`_anndata.py`): pearson_delta, mse, mae, mse_delta, mae_delta, discrimination_score, clustering_agreement, edistance
+- **DE metrics** (`_de.py`): overlap/precision at N, spearman correlations, direction match, significant gene recall, ROC/PR AUC
+
+### CLI
+
+Subcommands in `src/cell_eval/_cli/`: `prep` (data preparation for VCC), `run` (evaluation), `baseline` (create baseline), `score` (normalize against baseline). CLI defaults are in `_cli/_const.py`.
+
+### Test Data Utilities
+
+`cell_eval.data` provides `build_random_anndata()` and `downsample_cells()` for generating synthetic AnnData objects in tests.
+
+## Conventions
+
+- Uses `polars` (not pandas) for DataFrames
+- Uses `match`/`case` statements (Python 3.10+ syntax)
+- Type hints throughout; PEP 561 `py.typed` marker present
+- Private modules prefixed with `_` (public API is re-exported from `__init__.py`)

From 8901383f1d5b154c3ed9226d5b4c65e93c1c2612 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 11:43:56 -0800
Subject: [PATCH 12/18] chore(semver): bump - breaking changes

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index d1bba78..aba1108 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "cell-eval"
-version = "0.6.8"
+version = "0.7.0"
 description = "Evaluation metrics for single-cell perturbation predictions"
 readme = "README.md"
 authors = [

From 4984a711b1fffd02060c94bbda661bde2e542a4d Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 14:41:57 -0800
Subject: [PATCH 13/18] refactor: remove redundant code

---
 src/cell_eval/utils.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/src/cell_eval/utils.py b/src/cell_eval/utils.py
index 2b9f431..7828e74 100644
--- a/src/cell_eval/utils.py
+++ b/src/cell_eval/utils.py
@@ -125,7 +125,4 @@ def _cast_float16_to_float32(adata: ad.AnnData, which: str | None = None):
             logger.info(
                 f"Casting {which} anndata from float16 to float32 (NUMBA does not support float16)."
             )
-        if sp.issparse(x):
-            adata.X = x.astype(np.float32)
-        else:
-            adata.X = x.astype(np.float32)
+        adata.X = x.astype(np.float32)

From e7047a2a5fc97de82470067a54e26ba0de2094be Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 14:43:31 -0800
Subject: [PATCH 14/18] fix: deprecation warning on is_view

---
 src/cell_eval/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/cell_eval/utils.py b/src/cell_eval/utils.py
index 7828e74..8c6ae1e 100644
--- a/src/cell_eval/utils.py
+++ b/src/cell_eval/utils.py
@@ -40,7 +40,7 @@ def guess_is_lognorm(
     # Check for fractional values
     if isinstance(adata.X, csr_matrix) or isinstance(adata.X, csc_matrix):
         frac, _ = np.modf(adata.X.data)
-    elif adata.isview:
+    elif adata.is_view:
         frac, _ = np.modf(adata.X.toarray())  # type: ignore[unresolved-attribute]
     elif adata.X is None:
         raise ValueError("adata.X is None")

From 3e36c0ea26c6176454b135a8336a1218d03b924a Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Thu, 26 Feb 2026 14:45:18 -0800
Subject: [PATCH 15/18] dep: enforce anndata version

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index aba1108..0e6c69b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,6 +17,7 @@ dependencies = [
     "scanpy>=1.10.3",
     "pyarrow>=18.0.0",
     "tqdm>=4.67.1",
+    "anndata>=0.12.10",
 ]
 
 [build-system]

From 2d314f5064afa55f476ff1e6d6e5f16b741593e9 Mon Sep 17 00:00:00 2001
From: Beatrice Bevilacqua <beatrice.bevilacqua@arcinstitute.org>
Date: Thu, 5 Mar 2026 18:25:17 +0000
Subject: [PATCH 16/18] Use left join for DE Spearman/AUC

Fixes #227
---
 src/cell_eval/metrics/_de.py | 28 +++++++++++++++++-----------
 1 file changed, 17 insertions(+), 11 deletions(-)

diff --git a/src/cell_eval/metrics/_de.py b/src/cell_eval/metrics/_de.py
index 1f2ca00..bdae102 100644
--- a/src/cell_eval/metrics/_de.py
+++ b/src/cell_eval/metrics/_de.py
@@ -116,11 +116,15 @@ def __call__(self, data: DEComparison) -> dict[str, float]:
         """Compute correlation between log fold changes of significant genes."""
         correlations = {}
 
-        merged = data.real.filter_to_significant(fdr_threshold=self.fdr_threshold).join(
-            data.pred.data,
-            on=[data.real.target_col, data.real.feature_col],
-            suffix="_pred",
-            how="inner",
+        merged = (
+            data.real.filter_to_significant(fdr_threshold=self.fdr_threshold)
+            .join(
+                data.pred.data,
+                on=[data.real.target_col, data.real.feature_col],
+                suffix="_pred",
+                how="left",
+            )
+            .with_columns(pl.col(f"{data.real.fold_change_col}_pred").fill_null(0.0))
         )
 
         for row in (
@@ -224,17 +228,19 @@ def compute_generic_auc(
         (pl.col(real_fdr_col) < 0.05).cast(pl.Float32).alias("label")
     ).select([target_col, feature_col, "label"])
 
+    pred_q = pl.col(pred_fdr_col).fill_null(1.0).clip(1e-10, 1.0)
     merged = (
-        data.pred.data.select([target_col, feature_col, pred_fdr_col])
-        .join(
-            labeled_real,
+        labeled_real.join(
+            data.pred.data.select([target_col, feature_col, pred_fdr_col]),
             on=[target_col, feature_col],
-            how="inner",
+            how="left",
             coalesce=True,
         )
         .drop_nulls(["label"])
-        .with_columns((-pl.col(pred_fdr_col).replace(0, 1e-10).log10()).alias("nlp"))
-        .drop_nulls(["nlp"])
+        .with_columns(
+            pred_q.alias(pred_fdr_col),
+            (-pred_q.log10()).alias("nlp"),
+        )
     )
 
     results: dict[str, float] = {}

From ff5acaeea50b10eefb5ddf430b9733903a4609f8 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Tue, 24 Mar 2026 11:06:58 -0700
Subject: [PATCH 17/18] dep: remove upper limit on python version

---
 .python-version | 2 +-
 pyproject.toml  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.python-version b/.python-version
index e4fba21..6324d40 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.12
+3.14
diff --git a/pyproject.toml b/pyproject.toml
index 0e6c69b..17a79bd 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ authors = [
     { name = "Abhinav Adduri", email = "abhinav.adduri@arcinstitute.org" },
     { name = "Yusuf Roohani", email = "yusuf.roohani@arcinstitute.org" },
 ]
-requires-python = ">=3.11,<3.13"
+requires-python = ">=3.11"
 dependencies = [
     "igraph>=0.11.8",
     "pdex>=0.2.0",

From e629a20f9e783a527f8783730fd9993d9fc2bc48 Mon Sep 17 00:00:00 2001
From: noam teyssier <22600644+noamteyssier@users.noreply.github.com>
Date: Tue, 24 Mar 2026 11:08:36 -0700
Subject: [PATCH 18/18] ci: added more python versions to pytest

---
 .github/workflows/CI.yml | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index ffa890d..d889a64 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -78,6 +78,10 @@ jobs:
 
     needs: [install-job]
 
+    strategy:
+      matrix:
+        python-version: ["3.12", "3.13", "3.14"]
+
     steps:
       - uses: actions/checkout@v4
 
@@ -86,7 +90,7 @@ jobs:
         with:
           enable-cache: true
           cache-dependency-glob: "pyproject.toml"
-          python-version: "3.12"
+          python-version: "${{ matrix.python-version }}"
 
       - name: install dependencies
         run: |