deepcatch/pyproject.toml at main · rollroyces/deepcatch · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
[build-system]
requires = ["setuptools>=64", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "deepcatch"
version = "2.2.0"
description = "Mutation-informed ultra-sensitive cfDNA detection: panel-LLR, strand score, fisher, fragmentomics, GNN methylation, tissue deconvolution, and a REST API for clinical use."
readme = "README.md"
requires-python = ">=3.10"
license = {text = "MIT"}
authors = [
    {name = "Yu Ching Lam (Independent Researcher)"},
]
keywords = ["cfDNA", "ctDNA", "liquid-biopsy", "cancer-detection",
            "variant-calling", "panel-LLR", "fragmentomics", "methylation"]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Science/Research",
    "Intended Audience :: Healthcare Industry",
    "Topic :: Scientific/Engineering :: Bio-Informatics",
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Operating System :: MacOS",
    "Operating System :: POSIX :: Linux",
]

dependencies = [
    "numpy>=1.24.0",
    "scipy>=1.10.0",
    "scikit-learn>=1.3.0",
    "pandas>=2.0.0",
    "matplotlib>=3.7.0",
    "seaborn>=0.12.0",
    "requests>=2.31.0",
    "tqdm>=4.65.0",
]

[project.optional-dependencies]
# Neural model + GNN methylation + REST API
api = [
    "torch>=2.0.0",
    "torch-geometric>=2.4.0",
    "fastapi>=0.100.0",
    "uvicorn>=0.23.0",
    "pydantic>=2.0.0",
]
# Cross-repo consumption of the cfdna-fragmentomics-pipeline artifacts
tumor-naive = [
    "cfdna-fragmentomics-pipeline>=0.2.0",
]
# Development / testing
dev = [
    "pytest>=7.0.0",
    "pytest-cov>=4.0.0",
    "mypy>=1.5.0",
]

[project.urls]
"Source code" = "https://github.com/rollroyces/deepcatch"
"Paper" = "https://github.com/rollroyces/deepcatch/blob/main/paper/PAPER.md"
"Companion pipeline" = "https://github.com/rollroyces/cfdna-fragmentomics-pipeline"
"Issue tracker" = "https://github.com/rollroyces/deepcatch/issues"

[project.scripts]
# CLI entry points — installed automatically by `pip install`.
# Run as: `deepcatch-tumornaive`, `deepcatch-fusion`, etc.
#
# Note: deepcatch-tcga (the real-TCGA validator) is intentionally NOT
# a console_script — it lives at the repo root and downloads from the
# GDC API on first run. To run it directly:
#   python real_tcga_validation.py
# See `--help` for the full flag list.
deepcatch-tumornaive = "src.fragmentomics.train_tumor_naive:main"
deepcatch-fusion = "src.fragmentomics.fusion_ablation:main"
deepcatch-decisioncurve = "src.fragmentomics.decision_curve_cli:main"
# Note: deepcatch-aucgate is the synthetic-cohort smoke test. Run
# directly from the repo:
#   python scripts/adapter_auc_gate.py

[tool.setuptools]
packages = [
    "src",
    "src.fragmentomics",
    "src.preprocessing",
    "src.foundation",
    "src.ensemble",
    "src.clinical",
    "src.longitudinal",
    "src.methylation_gnn",
    "src.multimodal_fusion",
    "src.priming",
    "src.synthetic_data",
    "src.tissue_deconv",
    "src.variant_calling",
    "validation",
]
include-package-data = true

[tool.setuptools.package-data]
"src.fragmentomics" = ["*.npy"]
"validation" = ["**/*.csv", "**/*.tsv", "**/*.json"]

[tool.pytest.ini_options]
addopts = "-q --no-header"
testpaths = ["test"]
markers = [
    "slow: marks tests as slow (deselect with -m 'not slow')",
]