Initial commit: Chai-1 protein structure prediction pipeline for WES

- Nextflow pipeline using chai1 Docker image from Harbor
- S3-based input/output paths (s3://omic/eureka/chai-lab/)
- GPU-accelerated protein folding with MSA support

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

tests/test_msa_preprocess.py

@@ -0,0 +1,25 @@
+# Copyright (c) 2024 Chai Discovery, Inc.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for details.
+import torch
+
+from chai_lab.data.dataset.msas.msa_context import NO_PAIRING_KEY
+from chai_lab.data.dataset.msas.preprocess import _UKEY_FOR_QUERY, prepair_ukey
+
+
+def test_prepair_ukey():
+    keys = torch.tensor([1, 1, 2, 1, NO_PAIRING_KEY, 2, 3])
+    edit_dists = torch.arange(len(keys))
+
+    paired = prepair_ukey(keys, edit_dists)
+    assert list(paired) == [_UKEY_FOR_QUERY, (1, 0), (2, 0), (1, 1), (2, 1), (3, 0)]
+    assert set(paired.values()) == set(
+        [i for i, val in enumerate(keys.tolist()) if val != NO_PAIRING_KEY]
+    )
+
+    # Reverse the edit distances
+    paired = prepair_ukey(keys, torch.tensor(edit_dists.tolist()[::-1]))
+    assert list(paired) == [_UKEY_FOR_QUERY, (1, 1), (2, 1), (1, 0), (2, 0), (3, 0)]
+    assert set(paired.values()) == set(
+        [i for i, val in enumerate(keys.tolist()) if val != NO_PAIRING_KEY]
+    )