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_a3m_tokenization.py

@@ -0,0 +1,36 @@
+# Copyright (c) 2024 Chai Discovery, Inc.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for details.
+"""
+Test for tokenization
+"""
+
+import numpy as np
+
+from chai_lab.data.parsing.msas.a3m import tokenize_sequences_to_arrays
+from chai_lab.data.residue_constants import residue_types_with_nucleotides_order
+
+
+def test_tokenization_basic():
+    test_sequence = "RKDES"
+
+    out, dels = tokenize_sequences_to_arrays([test_sequence])
+    assert out.shape == dels.shape == (1, 5)
+    assert np.all(
+        out
+        == np.array(
+            [residue_types_with_nucleotides_order[res] for res in test_sequence]
+        )
+    )
+
+
+def test_tokenization_with_insertion():
+    """Insertions (lower case) should be ignored."""
+    test_sequence = "RKDES"
+    test_with_ins = "RKrkdesDES"
+
+    out, dels = tokenize_sequences_to_arrays([test_sequence, test_with_ins])
+    assert out.shape == dels.shape == (2, 5)
+    assert np.all(out[0] == out[1])
+    assert dels.sum() == 5
+    assert dels[1, 2] == 5