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biology/py-deeptools: User-friendly tools for exploring deep-sequencing data
deepTools contains useful modules to process the mapped reads data for multiple quality checks, creating normalized coverage files in standard bedGraph and bigWig file formats, that allow comparison between different files (for example, treatment and control). Finally, using such normalized and standardized files, deepTools can create many publication-ready visualizations to identify enrichments and for functional annotations of the genome.
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SUBDIR += py-bx-python
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SUBDIR += py-crossmap
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SUBDIR += py-cutadapt
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SUBDIR += py-deeptools
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SUBDIR += py-deeptoolsintervals
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SUBDIR += py-dnaio
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SUBDIR += py-ete3
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biology/py-deeptools/Makefile
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biology/py-deeptools/Makefile
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PORTNAME= deepTools
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DISTVERSION= 3.5.1
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CATEGORIES= biology python
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MASTER_SITES= CHEESESHOP
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PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
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MAINTAINER= jwb@FreeBSD.org
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COMMENT= User-friendly tools for exploring deep-sequencing data
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LICENSE= BSD3CLAUSE
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LICENSE_FILE= ${WRKSRC}/LICENSE.txt
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RUN_DEPENDS= ${PYNUMPY} \
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${PYTHON_PKGNAMEPREFIX}scipy>=0.17.0:science/py-scipy@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}matplotlib>=3.3.0:math/py-matplotlib@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}pysam>=0.14.0:biology/py-pysam@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}py2bit>=0.3.0:biology/py-py2bit@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}numpydoc>=0.5:textproc/py-numpydoc@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}pyBigWig>=0.3.18:biology/py-pybigwig@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}plotly>=4.9:graphics/py-plotly@${PY_FLAVOR} \
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${PYTHON_PKGNAMEPREFIX}deeptoolsintervals>=0.1.8:biology/py-deeptoolsintervals@${PY_FLAVOR}
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USES= python
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USE_PYTHON= autoplist concurrent distutils
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.include <bsd.port.mk>
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biology/py-deeptools/distinfo
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biology/py-deeptools/distinfo
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TIMESTAMP = 1617285775
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SHA256 (deepTools-3.5.1.tar.gz) = 62eea132513afa5f6bb51387e5866a5c3a26613aeb7e8c9600c38becf2ecb716
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SIZE (deepTools-3.5.1.tar.gz) = 199732
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biology/py-deeptools/pkg-descr
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biology/py-deeptools/pkg-descr
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deepTools contains useful modules to process the mapped reads data for
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multiple quality checks, creating normalized coverage files in standard
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bedGraph and bigWig file formats, that allow comparison between
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different files (for example, treatment and control). Finally, using
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such normalized and standardized files, deepTools can create many
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publication-ready visualizations to identify enrichments and for
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functional annotations of the genome.
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WWW: https://github.com/deeptools/deepTools
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