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‎README.rst‎

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@@ -29,7 +29,7 @@ Installation
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The following packages are required to run PyPGx:
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.. list-table:: Dependencies and their availability in Anaconda and PyPI
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.. list-table::
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:header-rows: 1
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* - Package
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CLI examples
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============
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Run NGS pipeline for CYP2D6:
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We can print the metadata of an archive file:
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.. code-block:: text
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$ pypgx print-metadata CYP2D6-copy-number.zip
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Above will print:
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.. code-block:: text
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Gene=CYP2D6
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Assembly=GRCh37
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SemanticType=CovFrame[CopyNumber]
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Platform=WGS
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Control=VDR
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Samples=None
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We can run the NGS pipeline for the *CYP2D6* gene:
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.. code-block:: text
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$ pypgx run-ngs-pipeline \
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CYP2D6 \
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CYP2D6-pipeline \
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--vcf input.vcf \
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--panel ref.vcf \
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--tsv input.tsv \
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--control-statistics control-statistics-VDR.zip
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$ pypgx run-ngs-pipeline \
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CYP2D6 \
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CYP2D6-pipeline \
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--vcf input.vcf \
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--panel ref.vcf \
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--tsv input.tsv \
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--control-statistics control-statistics-VDR.zip
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Above will create a number of archive files:
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.. code-block:: text
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Saved VcfFrame[Imported] to: CYP2D6-pipeline/imported-variants.zip
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Saved VcfFrame[Phased] to: CYP2D6-pipeline/phased-variants.zip
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Saved VcfFrame[Consolidated] to: CYP2D6-pipeline/consolidated-variants.zip
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Saved SampleTable[Alleles] to: CYP2D6-pipeline/alleles.zip
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Saved CovFrame[ReadDepth] to: CYP2D6-pipeline/read-depth.zip
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Saved CovFrame[CopyNumber] to: CYP2D6-pipeline/copy-number.zip
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Saved SampleTable[CNVCalls] to: CYP2D6-pipeline/cnv-calls.zip
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Saved SampleTable[Genotypes] to: CYP2D6-pipeline/genotypes.zip
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Saved SampleTable[Results] to: CYP2D6-pipeline/results.zip
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API examples
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============
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Predict phenotype based on two haplotype calls:
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We can obtain allele function for the *CYP2D6* gene:
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.. code:: python3
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>>> import pypgx
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>>> pypgx.get_function('CYP2D6', '*1')
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'Normal Function'
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>>> pypgx.get_function('CYP2D6', '*4')
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'No Function'
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>>> pypgx.get_function('CYP2D6', '*22')
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'Uncertain Function'
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>>> pypgx.get_function('CYP2D6', '*140')
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'Unknown Function'
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We can predict phenotype for the *CYP2D6* gene based on two haplotype calls:
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.. code:: python3
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'Indeterminate'
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>>> pypgx.predict_phenotype('CYP2D6', '*1', '*1x2') # Gene duplication
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'Ultrarapid Metabolizer'
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>>> pypgx.predict_phenotype('CYP2B6', '*1', '*4') # *4 has increased function
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'Rapid Metabolizer'

‎docs/create.py‎

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The following packages are required to run PyPGx:
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.. list-table:: Dependencies and their availability in Anaconda and PyPI
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.. list-table::
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:header-rows: 1
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* - Package
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CLI examples
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============
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Run NGS pipeline for CYP2D6:
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We can print the metadata of an archive file:
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.. code-block:: text
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$ pypgx print-metadata CYP2D6-copy-number.zip
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Above will print:
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.. code-block:: text
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Gene=CYP2D6
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Assembly=GRCh37
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SemanticType=CovFrame[CopyNumber]
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Platform=WGS
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Control=VDR
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Samples=None
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We can run the NGS pipeline for the *CYP2D6* gene:
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.. code-block:: text
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$ pypgx run-ngs-pipeline \\
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CYP2D6 \\
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CYP2D6-pipeline \\
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--vcf input.vcf \\
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--panel ref.vcf \\
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--tsv input.tsv \\
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--control-statistics control-statistics-VDR.zip
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$ pypgx run-ngs-pipeline \\
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CYP2D6 \\
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CYP2D6-pipeline \\
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--vcf input.vcf \\
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--panel ref.vcf \\
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--tsv input.tsv \\
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--control-statistics control-statistics-VDR.zip
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Above will create a number of archive files:
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.. code-block:: text
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Saved VcfFrame[Imported] to: CYP2D6-pipeline/imported-variants.zip
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Saved VcfFrame[Phased] to: CYP2D6-pipeline/phased-variants.zip
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Saved VcfFrame[Consolidated] to: CYP2D6-pipeline/consolidated-variants.zip
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Saved SampleTable[Alleles] to: CYP2D6-pipeline/alleles.zip
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Saved CovFrame[ReadDepth] to: CYP2D6-pipeline/read-depth.zip
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Saved CovFrame[CopyNumber] to: CYP2D6-pipeline/copy-number.zip
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Saved SampleTable[CNVCalls] to: CYP2D6-pipeline/cnv-calls.zip
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Saved SampleTable[Genotypes] to: CYP2D6-pipeline/genotypes.zip
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Saved SampleTable[Results] to: CYP2D6-pipeline/results.zip
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API examples
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============
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Predict phenotype based on two haplotype calls:
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We can obtain allele function for the *CYP2D6* gene:
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.. code:: python3
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>>> import pypgx
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>>> pypgx.get_function('CYP2D6', '*1')
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'Normal Function'
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>>> pypgx.get_function('CYP2D6', '*4')
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'No Function'
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>>> pypgx.get_function('CYP2D6', '*22')
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'Uncertain Function'
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>>> pypgx.get_function('CYP2D6', '*140')
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'Unknown Function'
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We can predict phenotype for the *CYP2D6* gene based on two haplotype calls:
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.. code:: python3
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'Indeterminate'
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>>> pypgx.predict_phenotype('CYP2D6', '*1', '*1x2') # Gene duplication
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'Ultrarapid Metabolizer'
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>>> pypgx.predict_phenotype('CYP2B6', '*1', '*4') # *4 has increased function
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'Rapid Metabolizer'
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""".format(**d)
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readme_file = f'{utils.PROGRAM_PATH}/README.rst'
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Introduction
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============
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This section describes software development kit (SDK) for PyPGx.
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This section describes the software development kit (SDK) for PyPGx.
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utils
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=====

‎docs/sdk.rst‎

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Introduction
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============
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This section describes software development kit (SDK) for PyPGx.
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This section describes the software development kit (SDK) for PyPGx.
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utils
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=====

‎docs/tutorials.rst‎

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@@ -36,7 +36,7 @@ Now that we have all the files we need, let's run the next-generation sequencing
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--tsv GeT-RM.tsv.gz \
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--control-statistics control-statistics-VDR.zip
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Above will create a number of archive files in the ``CYP2D6-pipeline`` directory:
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Above will create a number of archive files:
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.. code-block:: text
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‎pypgx/api/utils.py‎

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return sum([parsecnv(x) for x in allele.split('+')])
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def print_metadata(archive):
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def print_metadata(input):
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"""
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Print the metadata of specified archive.
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Parameters
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----------
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archive : pypgx.Archive
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input : pypgx.Archive
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Archive file.
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"""
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zf = zipfile.ZipFile(archive)
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zf = zipfile.ZipFile(input)
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parent = zf.filelist[0].filename.split('/')[0]
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with zf.open(f'{parent}/metadata.txt') as f:
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print(f.read().decode('utf-8').strip())

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