Merge branch 'master' into add-As1

Author: jonbrenas

malariagen_data/anoph/fst.py

@@ -1,3 +1,4 @@
+import warnings
 from typing import Tuple, Optional
 
 import numpy as np
@@ -43,6 +44,8 @@ def _fst_gwss(
         inline_array,
         chunks,
         clip_min,
+        min_snps_threshold,
+        window_adjustment_factor,
     ):
         # Compute allele counts.
         ac1 = self.snp_allele_counts(
@@ -81,6 +84,24 @@ def _fst_gwss(
                 chunks=chunks,
             ).compute()
 
+        n_snps = len(pos)
+        if n_snps < min_snps_threshold:
+            raise ValueError(
+                f"Too few SNP sites ({n_snps}) available for Fst GWSS. "
+                f"At least {min_snps_threshold} sites are required. "
+                "Try a larger genomic region or different site selection criteria."
+            )
+        if window_size >= n_snps:
+            adjusted_window_size = max(1, n_snps // window_adjustment_factor)
+            warnings.warn(
+                f"window_size ({window_size}) is >= the number of SNP sites "
+                f"available ({n_snps}); automatically adjusting window_size to "
+                f"{adjusted_window_size} (= {n_snps} // {window_adjustment_factor}).",
+                UserWarning,
+                stacklevel=2,
+            )
+            window_size = adjusted_window_size
+
         with self._spinner(desc="Compute Fst"):
             with np.errstate(divide="ignore", invalid="ignore"):
                 fst = allel.moving_hudson_fst(ac1, ac2, size=window_size)
@@ -96,8 +117,23 @@ def _fst_gwss(
     @doc(
         summary="""
             Run a Fst genome-wide scan to investigate genetic differentiation
-            between two cohorts.
+            between two cohorts. If window_size is >= the number of available
+            SNP sites, a UserWarning is issued and window_size is automatically
+            adjusted to number_of_snps // window_adjustment_factor. A ValueError
+            is raised if the number of available SNP sites is below
+            min_snps_threshold.
         """,
+        parameters=dict(
+            min_snps_threshold="""
+                Minimum number of SNP sites required. If fewer sites are
+                available a ValueError is raised.
+            """,
+            window_adjustment_factor="""
+                If window_size is >= the number of available SNP sites,
+                window_size is automatically set to
+                number_of_snps // window_adjustment_factor.
+            """,
+        ),
         returns=dict(
             x="An array containing the window centre point genomic positions",
             fst="An array with Fst statistic values for each window.",
@@ -123,6 +159,8 @@ def fst_gwss(
         inline_array: base_params.inline_array = base_params.inline_array_default,
         chunks: base_params.chunks = base_params.native_chunks,
         clip_min: fst_params.clip_min = 0.0,
+        min_snps_threshold: fst_params.min_snps_threshold = 1000,
+        window_adjustment_factor: fst_params.window_adjustment_factor = 10,
     ) -> Tuple[np.ndarray, np.ndarray]:
         # Change this name if you ever change the behaviour of this function, to
         # invalidate any previously cached data.
@@ -147,7 +185,13 @@ def fst_gwss(
             results = self.results_cache_get(name=name, params=params)
 
         except CacheMiss:
-            results = self._fst_gwss(**params, inline_array=inline_array, chunks=chunks)
+            results = self._fst_gwss(
+                **params,
+                inline_array=inline_array,
+                chunks=chunks,
+                min_snps_threshold=min_snps_threshold,
+                window_adjustment_factor=window_adjustment_factor,
+            )
             self.results_cache_set(name=name, params=params, results=results)
 
         x = results["x"]

malariagen_data/anoph/fst_params.py

@@ -34,6 +34,22 @@
     """,
 ]
 
+min_snps_threshold: TypeAlias = Annotated[
+    int,
+    """
+    Minimum number of SNP sites required for the Fst GWSS computation. If
+    fewer sites are available, a ValueError is raised.
+    """,
+]
+
+window_adjustment_factor: TypeAlias = Annotated[
+    int,
+    """
+    If window_size is >= the number of available SNP sites, the window_size
+    is automatically adjusted to number_of_snps // window_adjustment_factor.
+    """,
+]
+
 annotation: TypeAlias = Annotated[
     Optional[Literal["standard error", "Z score", "lower triangle"]],
     """

malariagen_data/anopheles.py

@@ -970,6 +970,12 @@ def plot_ihs_gwss_track(
             inline_array=inline_array,
         )
 
+        if len(x) == 0:
+            raise ValueError(
+                "No iHS values remain after filtering. "
+                "Try relaxing filter_min_maf or min_ehh parameters."
+            )
+
         # determine X axis range
         x_min = x[0]
         x_max = x[-1]
@@ -1494,6 +1500,12 @@ def plot_xpehh_gwss_track(
             inline_array=inline_array,
         )
 
+        if len(x) == 0:
+            raise ValueError(
+                "No XP-EHH values remain after filtering. "
+                "Try relaxing filter_min_maf or min_ehh parameters."
+            )
+
         # determine X axis range
         x_min = x[0]
         x_max = x[-1]

tests/anoph/test_fst.py

@@ -163,6 +163,52 @@ def test_fst_gwss(fixture, api: AnophelesFstAnalysis):
     assert isinstance(fig, bokeh.models.GridPlot)
 
 
+@parametrize_with_cases("fixture,api", cases=".")
+def test_fst_gwss_window_size_too_large(fixture, api: AnophelesFstAnalysis):
+    # When window_size exceeds available SNPs, a UserWarning must be issued and
+    # the function must still return a valid result using the adjusted window_size.
+    all_sample_sets = api.sample_sets()["sample_set"].to_list()
+    all_countries = api.sample_metadata()["country"].dropna().unique().tolist()
+    countries = np.random.choice(all_countries, size=2, replace=False).tolist()
+    cohort1_query = f"country == {countries[0]!r}"
+    cohort2_query = f"country == {countries[1]!r}"
+    with pytest.warns(UserWarning, match="window_size"):
+        x, fst = api.fst_gwss(
+            contig=str(np.random.choice(api.contigs)),
+            sample_sets=all_sample_sets,
+            cohort1_query=cohort1_query,
+            cohort2_query=cohort2_query,
+            site_mask=str(np.random.choice(api.site_mask_ids)),
+            window_size=10_000_000,  # far larger than any fixture SNP count
+            min_cohort_size=1,
+        )
+    assert isinstance(x, np.ndarray)
+    assert isinstance(fst, np.ndarray)
+    assert len(x) > 0
+    assert x.shape == fst.shape
+
+
+@parametrize_with_cases("fixture,api", cases=".")
+def test_fst_gwss_too_few_snps(fixture, api: AnophelesFstAnalysis):
+    # When min_snps_threshold exceeds available SNPs, a ValueError must be raised.
+    all_sample_sets = api.sample_sets()["sample_set"].to_list()
+    all_countries = api.sample_metadata()["country"].dropna().unique().tolist()
+    countries = np.random.choice(all_countries, size=2, replace=False).tolist()
+    cohort1_query = f"country == {countries[0]!r}"
+    cohort2_query = f"country == {countries[1]!r}"
+    with pytest.raises(ValueError, match="Too few SNP sites"):
+        api.fst_gwss(
+            contig=str(np.random.choice(api.contigs)),
+            sample_sets=all_sample_sets,
+            cohort1_query=cohort1_query,
+            cohort2_query=cohort2_query,
+            site_mask=str(np.random.choice(api.site_mask_ids)),
+            window_size=100,
+            min_cohort_size=1,
+            min_snps_threshold=10_000_000,  # far larger than any fixture SNP count (~28k-70k)
+        )
+
+
 @parametrize_with_cases("fixture,api", cases=".")
 def test_average_fst(fixture, api: AnophelesFstAnalysis):
     # Set up test parameters.