Update LD clumping to take loci with best p-value per bin. (#539)

Previously we were taking the max absolute value of beta, now we're
taking the best (lowest) p-value per bin.

python/python/bystro/prs/preprocess_for_prs.py

@@ -344,11 +344,16 @@ def select_max_effect_per_bin(scores_overlap_abs_val: pd.DataFrame) -> pd.DataFr
     ]
 
 
+def select_min_pval_per_bin(scores_overlap_abs_val: pd.DataFrame) -> pd.DataFrame:
+    """Select the row with the smallest p-value for each bin."""
+    return scores_overlap_abs_val.loc[scores_overlap_abs_val.groupby(["CHR", "bin"])["P"].idxmin()]
+
+
 def clean_scores_for_analysis(
-    max_effect_per_bin: pd.DataFrame, column_to_drop: str
+    min_pval_per_bin: pd.DataFrame, column_to_drop: str
 ) -> tuple[pd.DataFrame, pd.DataFrame]:
     """Drop extra columns and prepare df with final set of loci for dosage matrix filtering."""
-    scores_overlap_adjusted = max_effect_per_bin.drop(columns=["bin", "abs_effect_weight"])
+    scores_overlap_adjusted = min_pval_per_bin.drop(columns=["bin"])
     scores_overlap_adjusted = scores_overlap_adjusted.set_index("SNPID")
     format_col_index = scores_overlap_adjusted.columns.get_loc(column_to_drop)
     # If there is more than 1 column found, our "columns_to_keep" function will not work
@@ -370,9 +375,8 @@ def ld_clump(scores_overlap: pd.DataFrame, map_path: str) -> tuple[pd.DataFrame,
     )
     scores_overlap.insert(0, "allele_comparison", allele_comparison_results)
     scores_overlap_w_bins = assign_bins(scores_overlap, bin_mappings)
-    scores_overlap_abs_val = calculate_abs_effect_weights(scores_overlap_w_bins)
-    max_effect_per_bin = select_max_effect_per_bin(scores_overlap_abs_val)
-    return clean_scores_for_analysis(max_effect_per_bin, "ID_effect_as_ref")
+    min_pval_per_bin = select_min_pval_per_bin(scores_overlap_w_bins)
+    return clean_scores_for_analysis(min_pval_per_bin, "ID_effect_as_ref")
 
 
 def finalize_dosage_after_c_t(