Metadata-Version: 1.2
Name: cmdbtools
Version: 1.0.5
Summary: cmdbtools: A command line tools for CMDB variant browser.
Home-page: https://github.com/ShujiaHuang/cmdbtools
Author: Shujia Huang (at) BGI
Author-email: huangshujia@bgi.com
Maintainer: Shujia Huang (at) BGI
Maintainer-email: huangshujia@bgi.com
License: BSD (3-clause)
Download-URL: https://github.com/ShujiaHuang/cmdbtools
Description: 
        cmdbtools: A command line tools for CMDB varaints browser
        =========================================================
        
        Introduction
        ------------
        
        China is the most populous country and the second largest economy in the world. However, 
        the construction of Chinese genome database is in slow progress. At present, among the 
        world's large-scale international and national genome sequencing projects, such as 1KGP, 
        Genomics England, Genome of the Netherlands, ExAC are mostly biased towards the construction
        of a genomic baseline for European populations. In those projects, while the sample size goes
        up to hundreds of thousands for samples with european ancestry in those database, the sequen-
        cing Chinese samples is no more than a thousand.
        
        Since a high-quality genomic baseline database serves as an important control for medical 
        research and population-oriented clinical and drug applications, the Chinese millionome
        database (CMDB) is developed to fill the gap.
        
        The `Chinese Millionome Database(CMDB) <https://db.cngb.org/cmdb/>`_ is a unique large-scale 
        Chinese genomics database produced by BGI and hosted in the National GeneBank. The CMDB delivers
        peridical and useful variation information and scientific insights derived from the analysis of
        millions of Chinese sequencing data. The results aim to promote genetic research and precision
        medicine actions in China.
        
        The delivering information includes any of detected variants and the corresponding allele frequency,
        annotation, frequency comparison to the global populations from existing databases, etc.
        
        Benchmarking detail and methods are described in our *Cell* paper:
        
        Liu, S. et al.(2018) Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, 
        Patterns of Viral Infections, and Chinese Population History. *Cell*\ , 2, 347-359. 
        `DOI:https://doi.org/10.1016/j.cell.2018.08.016 <https://doi.org/10.1016/j.cell.2018.08.016>`_
        
        **cmdbtools** is a command line tool for this CMDB variants browser.
        
        Quick start
        -----------
        
        CMDB variant browser allows authorized access its data through an Genomics API and **cmdbtools** 
        is a convenient command line tools for this purpose.
        
        Installation
        ------------
        
        Install the released version by ``pip``\ :
        
        .. code-block:: bash
        
           pip install cmdbtools
        
        You may instead want to install the development version from github, by running:
        
        .. code-block:: bash
        
           pip install git+git://github.com/ShujiaHuang/cmdbtools.git#egg=cmdbtools
        
        Setup
        -----
        
        Please enable your API access from Profile in `CMDB browser <https://db.cngb.org/cmdb>`_ before using **cmdbtools**. 
        
        Login
        -----
        
        Login with ``cmdbtools`` by using CMDB API access key, which could be found from Profile->Genomics API if you have apply for it.
        
        
        .. image:: assets/figures/cmdb_genomics_api.png
           :target: assets/figures/cmdb_genomics_api.png
           :alt: cmdb_genomics_api
        
        
        .. code-block:: bash
        
           cmdbtools login -k your-genomics-api-key
        
        If everything goes smoothly, **means you can use CMDB as one of your varaints database in command line mode**.
        
        Logout
        ------
        
        Logout ``cmdbtools`` by simply run the command below:
        
        .. code-block:: bash
        
           cmdbtool logout
        
        Query a single variant
        ----------------------
        
        Variants could be retrieved from CMDB by using ``query-varaint``.
        
        Run ``cmdbtools query-variant -h`` to see all available options. There're two different ways to retrive variants.
        
        One is to use ``-c`` and ``-p`` parameters for single variant, the other way uses ``-l`` for multiple positions.
        
        Here are examples for quering single varaint by chromosome name and position.
        
        .. code-block:: bash
        
           cmdbtools query-variant -c chr17 -p 41234470
        
        and you will get something looks like below:
        
        .. code-block:: bash
        
           ##fileformat=VCFv4.2
           ##FILTER=<ID=LowQual,Description="Low quality">
           ##INFO=<ID=CMDB_AN,Number=1,Type=Integer,Description="Number of Alleles in Samples with Coverage from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_AC,Number=A,Type=Integer,Description="Alternate Allele Counts in Samples with Coverage from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_AF,Number=A,Type=Float,Description="Alternate Allele Frequencies from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_FILTER,Number=A,Type=Float,Description="Filter from CMDB_hg19_v1.0">
           #CHROM  POS ID  REF ALT QUAL    FILTER  INFO
           17  41234470    rs1060915&CD086610&COSM4416375  A   G   74.38   PASS    CMDB_AF=0.361763,CMDB_AC=4625,CMDB_AN=12757
        
        Quering multiple varants.
        -------------------------
        
        A list of variants could be retrieved from CMDB by using the parameters of ``-l`` when apply by ``query-varaint``.
        
        .. code-block:: bash
        
           cmdbtools query-variant -l positions.list > result.vcf
        
        Format for `positions.list <tests/positions.list>`_\ , could be a mixture of ``chrom   position`` and ``chrom    start   end``\ , even with or without ``chr`` in the
        chromosome ID column:
        
        .. code-block::
        
           #CHROM  POS
           chr22   17662378
           chr22   17662408
           22  17662442
           22  17662444
           22  17662699
           22  17662729
           22  17690496
           22  17662353    17663671
           22  17669209    17669357
        
        ``result.vcf`` is VCF format and looks like below:
        
        .. code-block::
        
           ##fileformat=VCFv4.2
           ##FILTER=<ID=LowQual,Description="Low quality">
           ##INFO=<ID=CMDB_AN,Number=1,Type=Integer,Description="Number of Alleles in Samples with Coverage from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_AC,Number=A,Type=Integer,Description="Alternate Allele Counts in Samples with Coverage from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_AF,Number=A,Type=Float,Description="Alternate Allele Frequencies from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_FILTER,Number=A,Type=Float,Description="Filter from CMDB_hg19_v1.0">
           #CHROM  POS ID  REF ALT QUAL    FILTER  INFO
           chr22   17662699    rs58754958  A   G   59.86   PASS    CMDB_AF=0.031047,CMDB_AC=441,CMDB_AN=13553
           chr22   17662793    rs7289170   A   G   64.23   PASS    CMDB_AF=0.050419,CMDB_AC=842,CMDB_AN=16135
           chr22   17669245    rs116020027 G   T   30.3    PASS    CMDB_AF=0.003453,CMDB_AC=43,CMDB_AN=11280
           chr22   17690409    rs362129    G   A   32.3    PASS    CMDB_AF=0.065438,CMDB_AC=686,CMDB_AN=10236
        
        Actrually you can use ``-c`` ``-p`` and ``-l`` simultaneously if you like. And ``positions.list`` could just contain one single position.
        
        .. code-block:: bash
        
           cmdbtools query-variant -c 22 -p 46616520 -l positions.list > result.vcf
        
        Annotate your VCF files
        -----------------------
        
        Annotate your VCF file with CMDB by using ``cmdbtools annotate`` command.
        
        Download a list of example variants in VCF format from `multiple_samples.vcf.gz <tests/multiple_samples.vcf.gz>`_.
        To annotate this list of variants with allele frequences from CMDB, you can just run the following command in Linux or Mac OS.
        
        .. code-block:: bash
        
           cmdbtools annotate -i multiple_samples.vcf.gz > multiple_samples_CMDB.vcf
        
        It'll take about 2 or 3 minutes to complete 3,000+ variants' annotation. Then you will get 4 new fields with the information of CMDB in VCF INFO:
        
        
        * ``CMDB_AF``\ : Allele frequece in CMDB;
        * ``CMDB_AN``\ : Coverage in CMDB in population level;
        * ``CMDB_AC``\ : Allele count in population level in CMDB;
        * ``CMDB_FILTER``\ : Filter status in CMDB.
        
        .. code-block:: bash
        
           ##fileformat=VCFv4.2
           ##ALT=<ID=NON_REF,Description="Represents any possible alternative allele at this location">
           ##FILTER=<ID=LowQual,Description="Low quality">
           ##INFO=<ID=AC,Number=A,Type=Integer,Description="Allele count in genotypes, for each ALT allele, in the same order as listed">
           ##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency, for each ALT allele, in the same order as listed">
           ##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
           ##INFO=<ID=BaseQRankSum,Number=1,Type=Float,Description="Z-score from Wilcoxon rank sum test of Alt Vs. Ref base qualities">
           ##reference=file:///home/tools/hg19_reference/ucsc.hg19.fasta
           ##INFO=<ID=CMDB_AN,Number=1,Type=Integer,Description="Number of Alleles in Samples with Coverage from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_AC,Number=A,Type=Integer,Description="Alternate Allele Counts in Samples with Coverage from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_AF,Number=A,Type=Float,Description="Alternate Allele Frequencies from CMDB_hg19_v1.0">
           ##INFO=<ID=CMDB_FILTER,Number=A,Type=Float,Description="Filter from CMDB_hg19_v1.0">
           #CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO
           chr21   9413612 .       C       T       6906.62 .       AC=25;AF=0.313;AN=80;BaseQRankSum=0.425;CMDB_AC=2459;CMDB_AF=0.207525;CMDB_AN=11834;CMDB_FILTER=PASS
           chr21   9413629 .       C       T       8028.88 .       AC=30;AF=0.375;AN=80;BaseQRankSum=-1.200e+00;CMDB_AC=6906;CMDB_AF=0.305445;CMDB_AN=22406;CMDB_FILTER=PASS
           chr21   9413700 .       G       A       7723.82 .       AC=30;AF=0.375;AN=80;BaseQRankSum=-9.000e-02
           chr21   9413735 .       C       A       10121.72        .       AC=35;AF=0.438;AN=80;BaseQRankSum=0.977;CMDB_AC=2385;CMDB_AF=0.283965;CMDB_AN=8382;CMDB_FILTER=PASS
           chr21   9413839 .       C       T       8192.08 .       AC=28;AF=0.350;AN=80;BaseQRankSum=-5.200e-02
           chr21   9413840 .       C       A       11514.35        .       AC=38;AF=0.475;AN=80;BaseQRankSum=0.253
           chr21   9413870 .       T       C       7390.60 .       AC=26;AF=0.325;AN=80;BaseQRankSum=-4.270e-01
           chr21   9413880 .       T       A       146.96  .       AC=1;AF=0.013;AN=80;BaseQRankSum=2.12;ClippingRankSum=0.00
           chr21   9413909 .       G       A       1131.78 .       AC=10;AF=0.125;AN=80;BaseQRankSum=0.549;CMDB_AC=209;CMDB_AF=0.01507;CMDB_AN=13683;CMDB_FILTER=PASS
           chr21   9413913 .       C       T       8120.65 .       AC=28;AF=0.350;AN=80;BaseQRankSum=-4.390e-01;CMDB_AC=2870;CMDB_AF=0.205597;CMDB_AN=13955;CMDB_FILTER=PASS
           chr21   9413945 .       T       C       43787.68        .       AC=71;AF=0.888;AN=80;BaseQRankSum=0.089
           chr21   9413995 .       C       T       9632.44 .       AC=29;AF=0.363;AN=80;BaseQRankSum=0.747
           chr21   9413996 .       A       G       41996.48        .       AC=71;AF=0.888;AN=80;BaseQRankSum=-1.242e+00;CMDB_AC=3308;CMDB_AF=0.688533;CMDB_AN=4790;CMDB_FILTER=PASS
           chr21   9414003 .       T       C       4256.54 .       AC=19;AF=0.238;AN=80;BaseQRankSum=-6.030e-01
        
        Citation
        --------
        
        **If you use CMDB in your scientific publication, we would appreciate citation this paper:**
        
        Siyang Liu, Shujia Huang. et al.(2018) Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, 
        Patterns of Viral Infections, and Chinese Population History. *Cell*\ , 2, 347-359. 
        `DOI:https://doi.org/10.1016/j.cell.2018.08.016 <https://doi.org/10.1016/j.cell.2018.08.016>`_
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
