fix(abundance): show raw intensities in bar chart column (#25)

Drop the log2 transform and y_min=0 from the BarChartColumn. With absolute
log2 values around 30, a real log2FC of 3 only translated to ~10% bar-height
difference, making bars look indistinguishable across samples. Plotting raw
intensities (with per-row auto-scaling) lets fold changes show up visually.

Co-authored-by: Claude <noreply@anthropic.com>

Author: t0mdavid-m

content/results_abundance.py

@@ -1,7 +1,6 @@
 """Abundance (ProteomicsLFQ) Results Page."""
 import streamlit as st
 import pandas as pd
-import numpy as np
 from pathlib import Path
 from src.common.common import page_setup
 from src.common.results_helpers import get_workflow_dir, get_abundance_data
@@ -71,10 +70,7 @@
         # Get sample columns (between stats and PeptideSequence)
         sample_cols = [c for c in pivot_df.columns if c not in ["ProteinName", "log2FC", "p-value", "PeptideSequence"]]
 
-        # Create bar chart column with log2-transformed values
-        pivot_df["Intensity"] = pivot_df[sample_cols].apply(
-            lambda row: [np.log2(v + 1) for v in row], axis=1
-        )
+        pivot_df["Intensity"] = pivot_df[sample_cols].apply(list, axis=1)
 
         # Reorder columns: place Intensity after p-value
         display_cols = ["ProteinName", "log2FC", "p-value", "Intensity"] + sample_cols + ["PeptideSequence"]
@@ -85,9 +81,8 @@
             column_config={
                 "Intensity": st.column_config.BarChartColumn(
                     "Intensity",
-                    help="Sample intensities (log2 scale)",
+                    help="Raw sample intensities",
                     width="small",
-                    y_min=0,
                 ),
             },
             use_container_width=True,