(optional) vertical orientation for marker presence plots

src/depiction_targeted_preproc/workflow/experimental.smk

@@ -64,6 +64,7 @@ rule qc_plot_marker_presence_mini:
         "python -m depiction_targeted_preproc.workflow.qc.plot_marker_presence"
         " --table-marker-distances-baseline {input.table_marker_distances_baseline}"
         " --table-marker-distances-calib {input.table_marker_distances_calib}"
+        " --layout-vertical"
         " --output-pdf {output.pdf}"
 
 variants_with_map = ["mass_cluster", "reg_shift"]

src/depiction_targeted_preproc/workflow/qc/plot_marker_presence.py

@@ -8,7 +8,7 @@
 from typer import Option
 
 
-def plot_marker_presence(df_peak_dist: pl.DataFrame, n_spectra: int, out_path: Path) -> None:
+def plot_marker_presence(df_peak_dist: pl.DataFrame, n_spectra: int, out_path: Path, layout_vertical:bool) -> None:
     # Add a `max_dist` column to the dataframe, that indicates the first bin a particular item falls into
     df = df_peak_dist.with_columns(abs_dist=pl.col("dist").abs()).sort("abs_dist")
     df_cutoffs = pl.DataFrame({"max_dist": [0.05, 0.1, 0.2, 0.3, 0.4, np.inf]}).sort("max_dist")
@@ -28,14 +28,15 @@ def plot_marker_presence(df_peak_dist: pl.DataFrame, n_spectra: int, out_path: P
         "fraction", descending=True
     )["label"]
 
+    layout_config = {"column": "variant:N"} if not layout_vertical else {"row": "variant:N"}
     c = (
         alt.Chart(df)
         .mark_bar()
         .encode(
             x=alt.X("sum(fraction):Q", scale=alt.Scale(domain=[0, 1])),
             y=alt.Y("label:N", sort=list(sorted_labels)),
             color=alt.Color("detection_dist:N"),
-            column="variant:N",
+            **layout_config
         )
         .properties(
             title="Fraction of spectra with peaks detected per marker at different max distance cutoffs", width=600
@@ -48,6 +49,7 @@ def qc_plot_marker_presence(
     table_marker_distances_baseline: Annotated[Path, Option()],
     table_marker_distances_calib: Annotated[Path, Option()],
     output_pdf: Annotated[Path, Option()],
+    layout_vertical: Annotated[bool, Option(is_flag=True)] = False,
 ) -> None:
     table_calib = pl.read_parquet(table_marker_distances_calib)
     table_baseline = pl.read_parquet(table_marker_distances_baseline)
@@ -57,7 +59,7 @@ def qc_plot_marker_presence(
             table_baseline.with_columns(variant=pl.lit("baseline_adj")),
         ]
     )
-    plot_marker_presence(df_peak_dist=table, n_spectra=table["i_spectrum"].n_unique(), out_path=output_pdf)
+    plot_marker_presence(df_peak_dist=table, n_spectra=table["i_spectrum"].n_unique(), out_path=output_pdf, layout_vertical=layout_vertical)
 
 
 if __name__ == "__main__":