MATES-0.1.2-20240813-foss-2023a-CUDA-12.1.1.eb

easyblock = 'PythonBundle'

name = 'MATES'
version = '0.1.2-20240813'
local_commit = 'd5ee15b'
versionsuffix = '-CUDA-%(cudaver)s'

homepage = 'https://github.com/mcgilldinglab/MATES'
description = "A Deep Learning-Based Model for Quantifying Transposable Elements in Single-Cell Sequencing Data."

toolchain = {'name': 'foss', 'version': '2023a'}

dependencies = [
    ('Python', '3.11.3'),
    ('CUDA', '12.1.1', '', SYSTEM),
    ('Python-bundle-PyPI', '2023.06'),
    ('SciPy-bundle', '2023.07'),
    ('matplotlib', '3.7.2'),
    ('anndata', '0.10.5.post1'),
    ('SAMtools', '1.18'),
    ('pybedtools', '0.9.1'),
    ('PyTorch-bundle', '2.1.2', versionsuffix),
    ('Pysam', '0.22.0'),
    ('tqdm', '4.66.1'),
]

use_pip = True
sanity_pip_check = True

exts_list = [
    ('sorted_nearest', '0.0.39', {
        'checksums': ['16a51d5db87ae226b47ace43c176bb672477a1b7ba8052ea9291a6356c9c69b1'],
    }),
    ('ncls', '0.0.68', {
        'checksums': ['81aaa5abb123bb21797ed2f8ef921e20222db14a3ecbc61ccf447532f2b7ba93'],
    }),
    ('natsort', '8.4.0', {
        'checksums': ['45312c4a0e5507593da193dedd04abb1469253b601ecaf63445ad80f0a1ea581'],
    }),
    ('pyranges', '0.0.129', {
        'checksums': ['bee83b4fad0062be9586668c6b0fc4270d5e761951975e018202993680071fb3'],
    }),
    (name, version, {
        'modulename': 'MATES',
        # unpin exact versions of dependencies
        'preinstallopts': r"sed -i 's/==.*//g' requirements.txt && sed -i 's/==.*/\",/g' setup.py && ",
        'source_urls': ['https://github.com/mcgilldinglab/MATES/archive'],
        'sources': [{'download_filename': '%s.tar.gz' % local_commit, 'filename': SOURCE_TAR_GZ}],
        'checksums': ['aca36b2b99ebed975fdf61670a9b551c1ab7882ff2b9d4ed3f25f2e13805652c'],
    }),
]

sanity_check_commands = [
    "python -c 'from MATES import bam_processor, data_processor, MATES_model'",
    "python -c 'from MATES import TE_quantifier, TE_quantifier_LongRead, TE_quantifier_Intronic'",
]

moduleclass = 'bio'