Update evo opp threshold

Author: Haddox

notebooks/compute_rates.ipynb

@@ -470,12 +470,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Compute genome-wide rates, grouping data across all subtypes. Only analyze mutations with an evolutionary opportunity >1, corresponding to 1 mutation count per site in a segment across all branches where a mutation was possible. This focuses on the mutations with the most data (though results do not really change if all mutations are included)."
+    "Compute genome-wide rates, grouping data across all subtypes. Only analyze mutations with an evolutionary opportunity >0.1, corresponding to 0.1 synonymous mutation count per site in a segment across all branches where a mutation was possible. This focuses on the mutations with the most data (though results do not really change if all mutations are included)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2026-03-09T18:48:57.969616Z",
@@ -605,7 +605,7 @@
    ],
    "source": [
     "# Compute genome-wide rates for each host category (all, human, avian)\n",
-    "genome_wide_evo_opp_threshold = 1.0\n",
+    "genome_wide_evo_opp_threshold = 0.1\n",
     "genome_wide_rates = (\n",
     "    counts_df[counts_df['evo_opp'] > genome_wide_evo_opp_threshold]\n",
     "    .groupby(['mut_type', 'mut_class', 'host'])[['actual_count', 'evo_opp']].sum()\n",
@@ -1613,7 +1613,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.18"
+   "version": "3.13.12"
   }
  },
  "nbformat": 4,