Debugging a section of the code/phenotype for the GWAS, added slides to further delve into interpretting genetic data files.

Exercises/data/Tutorial_Phenotype.txt

@@ -1,159 +1,159 @@
-NA18646	2
-HG02178	2
-HG04063	2
-NA20901	1
-HG03046	2
-HG00457	1
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-HG03105	2
-HG02854	1
-NA20845	1
-NA18988	1
-HG02137	1
-HG01522	2
-NA21122	2
-HG03354	2
-HG03478	1
-NA19786	1
-NA20346	1
-HG03352	1
-HG03074	1
-HG00689	1
-HG02298	2
-HG03267	2
-HG04161	1
-NA12717	2
-NA18591	2
-NA20872	2
-HG01308	1
-HG03953	1
-NA18597	2
-HG02332	1
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-HG00114	1
-NA12716	1
-NA19652	1
-HG03097	2
-NA18638	1
-NA20881	2
-HG03058	2
-HG03082	2
-HG04209	2
-NA18544	1
-HG03073	2
-HG00445	1
-NA21089	2
-HG04185	1
-NA18630	2
-HG02804	1
-HG03729	1
-NA19377	2
-HG03436	1
-NA18948	1
-HG01253	1
-HG02787	2
-HG00381	2
-HG01631	1
-HG02009	1
-HG02661	2
-NA19072	1
-HG00173	2
-NA20508	2
-NA20850	1
-NA19393	1
-HG03297	2
-HG00449	2
-HG02771	1
-NA20822	2
-HG00566	2
-NA20867	1
-HG01512	1
-HG03511	2
-HG02390	1
-HG01680	1
-NA18941	2
-NA18962	1
-NA18561	1
-HG01537	2
-HG01072	1
-HG01536	1
-NA19324	2
-NA19782	2
-HG01971	2
-HG03730	2
-HG00246	1
-HG01113	2
-HG02651	1
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-NA20542	2
-HG01613	2
-HG00121	2
-HG04107	1
-HG02301	2
-HG03977	2
-HG01351	2
-HG03009	1
-HG02977	1
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-HG01700	1
-HG02040	1
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-HG01932	1
-NA18639	1
-NA07347	1
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-HG01130	1
-NA20799	2
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-NA19023	2
-HG02508	2
-HG02731	2
-HG03829	2
-HG02322	2
-HG02645	1
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-HG03133	1
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-HG01095	2
-NA18510	1
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-NA19087	2
-NA18874	1
-NA19449	2
-NA18574	2
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+NA20845	0
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+HG02137	0
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+NA18591	1
+NA20872	1
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+HG03953	0
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+NA20881	1
+HG03058	1
+HG03082	1
+HG04209	1
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+HG03073	1
+HG00445	0
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+HG04185	0
+NA18630	1
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+HG03729	0
+NA19377	1
+HG03436	0
+NA18948	0
+HG01253	0
+HG02787	1
+HG00381	1
+HG01631	0
+HG02009	0
+HG02661	1
+NA19072	0
+HG00173	1
+NA20508	1
+NA20850	0
+NA19393	0
+HG03297	1
+HG00449	1
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+NA20822	1
+HG00566	1
+NA20867	0
+HG01512	0
+HG03511	0
+HG02390	0
+HG01680	0
+NA18941	1
+NA18962	0
+NA18561	0
+HG01537	1
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+HG01536	0
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+HG01113	1
+HG02651	0
+NA19670	0
+HG02380	0
+NA20542	1
+HG01613	1
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+HG04107	0
+HG02301	1
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+NA19118	1
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+NA20875	1
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+HG01070	1
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Exercises/scripts/Tutorial_Key.ipynb

@@ -25,9 +25,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install gdown\n",
-    "!gdown \"https://drive.google.com/uc?id=1iwJi7QfF3LElnCPen4fEQVoY4Vk4A9_5\"\n",
-    "!tar -xzvf TUTORIAL.tar.gz"
+    "!wget -nc https://hgdownload.soe.ucsc.edu/goldenPath/currentGenomes/Homo_sapiens/bigZips/hg38.fa.gz"
    ]
   },
   {
@@ -252,32 +250,35 @@
     "    lo = LiftOver(chain_file)\n",
     "    n_variants = len(variant_data['CHROM'])\n",
     "    unmapped_mask = np.zeros(n_variants, dtype=bool)\n",
-    "    \n",
-    "    # Create copies to avoid modifying original data\n",
+    "\n",
     "    new_chroms = variant_data['CHROM'].copy()\n",
     "    new_positions = variant_data['POS'].copy()\n",
-    "    \n",
+    "\n",
     "    for i, (chrom, pos) in enumerate(zip(variant_data['CHROM'], variant_data['POS'])):\n",
     "        chrom_clean = chrom.replace('chr', '')\n",
-    "        lifted = lo.convert_coordinate(f'chr{chrom_clean}', pos - 1)  # Convert to 0-based\n",
-    "        \n",
+    "        lifted = lo.convert_coordinate(f'chr{chrom_clean}', pos - 1)\n",
+    "\n",
     "        if not lifted:\n",
     "            unmapped_mask[i] = True\n",
     "        else:\n",
-    "            # Update with lifted coordinates\n",
     "            lifted_result = lifted[0]\n",
-    "            lifted_chrom = lifted_result[0]\n",
-    "            lifted_pos = lifted_result[1]\n",
-    "            new_chroms[i] = lifted_chrom\n",
-    "            new_positions[i] = lifted_pos + 1  # Convert back to 1-based\n",
-    "    \n",
-    "    # Update variant_data with new coordinates\n",
+    "            new_chroms[i] = lifted_result[0]\n",
+    "            new_positions[i] = lifted_result[1] + 1\n",
+    "\n",
     "    variant_data_lifted = variant_data.copy()\n",
     "    variant_data_lifted['CHROM'] = new_chroms\n",
     "    variant_data_lifted['POS'] = new_positions\n",
-    "    \n",
-    "    # Filter out unmapped variants\n",
-    "    return filter_variants(variant_data_lifted, sample_metadata, ~unmapped_mask)\n"
+    "\n",
+    "    # Keep only successfully mapped variants -- filter directly, don't\n",
+    "    # route through filter_variants' missingness threshold\n",
+    "    keep_mask = ~unmapped_mask\n",
+    "    filtered_variants = {k: v[keep_mask] for k, v in variant_data_lifted.items()}\n",
+    "    filtered_samples = {\n",
+    "        'samples': sample_metadata['samples'],\n",
+    "        'sex': sample_metadata['sex'],\n",
+    "        'genotypes': sample_metadata['genotypes'][keep_mask]\n",
+    "    }\n",
+    "    return filtered_variants, filtered_samples"
    ]
   },
   {