Metadata-Version: 1.2
Name: pysradb
Version: 1.1.0
Summary: A Python package for interacting with SRAdb and downloading datasets from SRA/ENA/GEO
Home-page: https://github.com/saketkc/pysradb
Author: Saket Choudhary
Author-email: saketkc@gmail.com
License: BSD license
Description: ######################################################################################
        A Python package for retrieving metadata and downloading datasets from SRA/ENA/GEO
        ######################################################################################
        
        .. image:: https://img.shields.io/pypi/v/pysradb.svg?style=flat-square
            :target: https://pypi.python.org/pypi/pysradb
        
        .. image:: https://anaconda.org/bioconda/pysradb/badges/version.svg
            :target: https://anaconda.org/bioconda/pysradb/badges/version.svg
            
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        .. image:: https://zenodo.org/badge/159590788.svg
            :target: https://zenodo.org/badge/latestdoi/159590788
        
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            :target: https://github.com/saketkc/pysradb/actions
           
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        *************
        Documentation
        *************
        
        https://saketkc.github.io/pysradb
        
        
        *********
        CLI Usage
        *********
        
        ``pysradb`` supports command line ussage. See `CLI <https://saket-choudhary.me/pysradb/cmdline.html>`_ instructions or  `quickstart guide <https://www.saket-choudhary.me/pysradb/quickstart.html>`_.
         
        
        
        ::
        
           $ pysradb
            usage: pysradb [-h] [--version] [--citation]
                           {metadata,download,search,gse-to-gsm,gse-to-srp,gsm-to-gse,gsm-to-srp,gsm-to-srr,gsm-to-srs,gsm-to-srx,srp-to-gse,srp-to-srr,srp-to-srs,srp-to-srx,srr-to-gsm,srr-to-srp,srr-to-srs,srr-to-srx,srs-to-gsm,srs-to-srx,srx-to-srp,srx-to-srr,srx-to-srs}
                           ...
        
            pysradb: Query NGS metadata and data from NCBI Sequence Read Archive.
            version: 1.0.1
            Citation: 10.12688/f1000research.18676.1
        
            optional arguments:
              -h, --help            show this help message and exit
              --version             show program's version number and exit
              --citation            how to cite
        
            subcommands:
              {metadata,download,search,gse-to-gsm,gse-to-srp,gsm-to-gse,gsm-to-srp,gsm-to-srr,gsm-to-srs,gsm-to-srx,srp-to-gse,srp-to-srr,srp-to-srs,srp-to-srx,srr-to-gsm,srr-to-srp,srr-to-srs,srr-to-srx,srs-to-gsm,srs-to-srx,srx-to-srp,srx-to-srr,srx-to-srs}
                metadata            Fetch metadata for SRA project (SRPnnnn)
                download            Download SRA project (SRPnnnn)
                search              Search SRA for matching text
                gse-to-gsm          Get GSM for a GSE
                gse-to-srp          Get SRP for a GSE
                gsm-to-gse          Get GSE for a GSM
                gsm-to-srp          Get SRP for a GSM
                gsm-to-srr          Get SRR for a GSM
                gsm-to-srs          Get SRS for a GSM
                gsm-to-srx          Get SRX for a GSM
                srp-to-gse          Get GSE for a SRP
                srp-to-srr          Get SRR for a SRP
                srp-to-srs          Get SRS for a SRP
                srp-to-srx          Get SRX for a SRP
                srr-to-gsm          Get GSM for a SRR
                srr-to-srp          Get SRP for a SRR
                srr-to-srs          Get SRS for a SRR
                srr-to-srx          Get SRX for a SRR
                srs-to-gsm          Get GSM for a SRS
                srs-to-srx          Get SRX for a SRS
                srx-to-srp          Get SRP for a SRX
                srx-to-srr          Get SRR for a SRX
                srx-to-srs          Get SRS for a SRX
        
        
        **********
        Quickstart
        **********
        
        A Google Colaboratory version of most used commands are available in this `Colab Notebook <https://colab.research.google.com/drive/1C60V-jkcNZiaCra_V5iEyFs318jgVoUR>`_ . Note that this requires only an active internet connection (no additional downloads are made).
        
        The following notebooks document all the possible features of `pysradb`:
        
        1. `Python API <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/01.Python-API_demo.ipynb>`_
        2. `Downloading datasets from SRA - command line <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/02.Commandline_download.ipynb>`_
        3. `Parallely download multiple datasets - Python API <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/03.ParallelDownload.ipynb>`_
        4. `Converting SRA-to-fastq - command line (requires conda) <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/04.SRA_to_fastq_conda.ipynb>`_
        5. `Downloading subsets of a project - Python API <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/05.Downloading_subsets_of_a_project.ipynb>`_
        6. `Download BAMs <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/06.Download_BAMs.ipynb>`_
        7. `Metadata for multiple SRPs <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/07.Multiple_SRPs.ipynb>`_
        8. `Multithreaded fastq downloads using Aspera Client <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/08.pysradb_ascp_multithreaded.ipynb>`_
        9. `Searching SRA/GEO/ENA <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/09.Query_Search.ipynb>`_
        
        
        
        ************
        Installation
        ************
        
        
        To install stable version using `pip`:
        
        .. code-block:: bash
        
           pip install pysradb
        
        Alternatively, if you use conda:
        
        .. code-block:: bash
        
           conda install -c bioconda pysradb
        
        This step will install all the dependencies.
        If you have an existing environment with a lot of pre-installed packages, conda might be `slow <https://github.com/bioconda/bioconda-recipes/issues/13774>`_.
        Please consider creating a new enviroment for ``pysradb``:
        
        .. code-block:: bash
        
           conda create -c bioconda -n pysradb PYTHON=3.7 pysradb
        
        Dependecies
        ===========
        
        .. code-block:: bash
        
           pandas
           requests
           tqdm
           xmltodict
        
        
        Installing pysradb in development mode
        ======================================
        
        .. code-block:: bash
        
           git clone https://github.com/saketkc/pysradb.git
           cd pysradb && pip install -r requirements.txt
           pip install -e .
        
        
        
        *************
        Using pysradb
        *************
        
        
        
        Obtaining SRA metadata
        ======================
        
        ::
        
            $ pysradb metadata SRP000941 | head
        
            study_accession experiment_accession experiment_title                                                                                                                 experiment_desc                                                                                                                  organism_taxid  organism_name library_strategy library_source  library_selection sample_accession sample_title instrument                    total_spots total_size    run_accession run_total_spots run_total_bases
            SRP000941       SRX056722                                                                         Reference Epigenome: ChIP-Seq Analysis of H3K27ac in hESC H1 Cells                                                               Reference Epigenome: ChIP-Seq Analysis of H3K27ac in hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC    ChIP            SRS184466                              Illumina HiSeq 2000    26900401     531654480   SRR179707     26900401         807012030
            SRP000941       SRX027889                                                                            Reference Epigenome: ChIP-Seq Analysis of H2AK5ac in hESC Cells                                                                  Reference Epigenome: ChIP-Seq Analysis of H2AK5ac in hESC Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC    ChIP            SRS116481                      Illumina Genome Analyzer II    37528590     779578968   SRR067978     37528590        1351029240
            SRP000941       SRX027888                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS116483                      Illumina Genome Analyzer II    13603127    3232309537   SRR067977     13603127         489712572
            SRP000941       SRX027887                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS116562                      Illumina Genome Analyzer II    22430523     506327844   SRR067976     22430523         807498828
            SRP000941       SRX027886                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS116560                      Illumina Genome Analyzer II    15342951     301720436   SRR067975     15342951         552346236
            SRP000941       SRX027885                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS116482                      Illumina Genome Analyzer II    39725232     851429082   SRR067974     39725232        1430108352
            SRP000941       SRX027884                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS116481                      Illumina Genome Analyzer II    32633277     544478483   SRR067973     32633277        1174797972
            SRP000941       SRX027883                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS004118                      Illumina Genome Analyzer II    22150965    3262293717   SRR067972      9357767         336879612
            SRP000941       SRX027883                                                                                     Reference Epigenome: ChIP-Seq Input from hESC H1 Cells                                                                           Reference Epigenome: ChIP-Seq Input from hESC H1 Cells  9606            Homo sapiens       ChIP-Seq           GENOMIC  RANDOM            SRS004118                      Illumina Genome Analyzer II    22150965    3262293717   SRR067971     12793198         460555128
        
        
        Obtaining detailed SRA metadata
        ===============================
        
        ::
        
            $ pysradb metadata SRP075720 --detailed | head
        
            study_accession experiment_accession experiment_title                                  experiment_desc                                   organism_taxid  organism_name library_strategy library_source  library_selection sample_accession sample_title instrument           total_spots total_size run_accession run_total_spots run_total_bases
            SRP075720       SRX1800476            GSM2177569: Kcng4_2la_H9; Mus musculus; RNA-Seq   GSM2177569: Kcng4_2la_H9; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467643                    Illumina HiSeq 2500  2547148      97658407  SRR3587912    2547148         127357400
            SRP075720       SRX1800475            GSM2177568: Kcng4_2la_H8; Mus musculus; RNA-Seq   GSM2177568: Kcng4_2la_H8; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467642                    Illumina HiSeq 2500  2676053     101904264  SRR3587911    2676053         133802650
            SRP075720       SRX1800474            GSM2177567: Kcng4_2la_H7; Mus musculus; RNA-Seq   GSM2177567: Kcng4_2la_H7; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467641                    Illumina HiSeq 2500  1603567      61729014  SRR3587910    1603567          80178350
            SRP075720       SRX1800473            GSM2177566: Kcng4_2la_H6; Mus musculus; RNA-Seq   GSM2177566: Kcng4_2la_H6; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467640                    Illumina HiSeq 2500  2498920      94977329  SRR3587909    2498920         124946000
            SRP075720       SRX1800472            GSM2177565: Kcng4_2la_H5; Mus musculus; RNA-Seq   GSM2177565: Kcng4_2la_H5; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467639                    Illumina HiSeq 2500  2226670      83473957  SRR3587908    2226670         111333500
            SRP075720       SRX1800471            GSM2177564: Kcng4_2la_H4; Mus musculus; RNA-Seq   GSM2177564: Kcng4_2la_H4; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467638                    Illumina HiSeq 2500  2269546      87486278  SRR3587907    2269546         113477300
            SRP075720       SRX1800470            GSM2177563: Kcng4_2la_H3; Mus musculus; RNA-Seq   GSM2177563: Kcng4_2la_H3; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467636                    Illumina HiSeq 2500  2333284      88669838  SRR3587906    2333284         116664200
            SRP075720       SRX1800469            GSM2177562: Kcng4_2la_H2; Mus musculus; RNA-Seq   GSM2177562: Kcng4_2la_H2; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467637                    Illumina HiSeq 2500  2071159      79689296  SRR3587905    2071159         103557950
            SRP075720       SRX1800468            GSM2177561: Kcng4_2la_H1; Mus musculus; RNA-Seq   GSM2177561: Kcng4_2la_H1; Mus musculus; RNA-Seq  10090           Mus musculus  RNA-Seq          TRANSCRIPTOMIC  cDNA              SRS1467635                    Illumina HiSeq 2500  2321657      89307894  SRR3587904    2321657         116082850
        
        
        
        Converting SRP to GSE
        =====================
        
        ::
        
            $ pysradb srp-to-gse SRP075720
        
            study_accession study_alias
            SRP075720       GSE81903
        
        
        Converting GSM to SRP
        =====================
        
        ::
        
            $ pysradb gsm-to-srp GSM2177186
        
            experiment_alias study_accession
            GSM2177186       SRP075720
        
        
        Converting GSM to GSE
        =====================
        
        ::
        
            $ pysradb gsm-to-gse GSM2177186
        
            experiment_alias study_alias
            GSM2177186       GSE81903
        
        
        Converting GSM to SRX
        =====================
        
        ::
        
            $ pysradb gsm-to-srx GSM2177186
        
            experiment_alias experiment_accession
            GSM2177186       SRX1800089
        
        
        Converting GSM to SRR
        =====================
        
        ::
        
            $ pysradb gsm-to-srr GSM2177186
        
            experiment_alias run_accession
            GSM2177186       SRR3587529
        
        
        Downloading supplementary files from GEO
        ========================================
        
        ::
        
            $ pysradb download -g GSE161707
            
        
        Downloading an entire SRA/ENA project (multithreaded)
        =====================================================
        
        ``pysradb`` makes it super easy to download datasets from SRA parallely:
        Using 8 threads to download:
        
        ::
        
            $ pysradb download -y -t 8 --out-dir ./pysradb_downloads -p SRP063852
        
        Downloads are organized by ``SRP/SRX/SRR`` mimicking the hiererachy of SRA projects.
        
        
        Downloading only certain samples of interest
        ============================================
        
        ::
        
            $ pysradb metadata SRP000941 --detailed | grep 'study\|RNA-Seq' | pysradb download
        
        This will download all ``RNA-seq`` samples coming from this project.
        
        
        Ultrafast fastq downloads
        =========================
        
        With `aspera-client <https://downloads.asperasoft.com/en/downloads/8?list>`_ installed, `pysradb` can perform ultra fast downloads:
        
        To download all original fastqs with `aspera-client` installed utilizing 8 threads:
        
        ::
        
            $ pysradb download -t 8 --use_ascp -p SRP002605
        
        Refer to the notebook for `(shallow) time benchmarks <https://colab.research.google.com/github/saketkc/pysradb/blob/master/notebooks/08.pysradb_ascp_multithreaded.ipynb>`_.
        
        
        
        
        ***********
        Publication
        ***********
        
         `pysradb: A Python package to query next-generation sequencing metadata and data from NCBI Sequence Read Archive <https://f1000research.com/articles/8-532/v1>`_
        
        
         Presentation slides from BOSC (ISMB-ECCB) 2019: https://f1000research.com/slides/8-1183
        
        
        ********
        Citation
        ********
        
        Choudhary, Saket. "pysradb: A Python Package to Query next-Generation Sequencing Metadata and Data from NCBI Sequence Read Archive." F1000Research, vol. 8, F1000 (Faculty of 1000 Ltd), Apr. 2019, p. 532 (https://f1000research.com/articles/8-532/v1)
        
        ::
        
            @article{Choudhary2019,
            doi = {10.12688/f1000research.18676.1},
            url = {https://doi.org/10.12688/f1000research.18676.1},
            year = {2019},
            month = apr,
            publisher = {F1000 (Faculty of 1000 Ltd)},
            volume = {8},
            pages = {532},
            author = {Saket Choudhary},
            title = {pysradb: A {P}ython package to query next-generation sequencing metadata and data from {NCBI} {S}equence {R}ead {A}rchive},
            journal = {F1000Research}
            }
        
        
        Zenodo archive: https://zenodo.org/badge/latestdoi/159590788
        
        Zenodo DOI: 10.5281/zenodo.2306881
        
        
        **********
        Questions?
        **********
        
        Join our `Slack Channel <https://join.slack.com/t/pysradb/shared_invite/zt-f01jndpy-KflPu3Be5Aq3FzRh5wj1Ug>`_ or open an `issue <https://github.com/saketkc/pysradb/issues>`_.
        
        
        #######
        History
        #######
        
        *******************
        1.1.0 (12-12-2021)
        *******************
        * Fixed `gsm-to-gse` failure (`#128 <https://github.com/saketkc/pysradb/pull/128>`_)
        * Fixed case sensitivity bug for ENA search (`#144 <https://github.com/saketkc/pysradb/pull/144>`_)
        * Fixed publication date bug for search (`#146 <https://github.com/saketkc/pysradb/pull/146>`_)
        * Added support for downloading data from GEO `pysradb dowload -g <GSE>` (`#129 <https://github.com/saketkc/pysradb/pull/129>`_)
        
        *******************
        1.0.1 (01-10-2021)
        *******************
        * Dropped Python 3.6 since pandas 1.2 is not supported
        
        *******************
        1.0.0 (01-09-2021)
        *******************
        * Retired ``metadb`` and ``SRAdb`` based search through CLI - everything defaults to ``SRAweb``
        * ``SRAweb`` now supports `search <https://saket-choudhary.me/pysradb/quickstart.html#search>`_
        * `N/A` is now replaced with `pd.NA`
        * Two new fields in `--detailed`: `instrument_model` and `instrument_model_desc` `#75 <https://github.com/saketkc/pysradb/issues/75>`_
        * Updated documentation
        
        *******************
        0.11.1 (09-18-2020)
        *******************
        * `library_layout` is now outputted in metadata #56
        *  `-detailed` unifies columns for ENA fastq links instead of appending _x/_y #59
        * bugfix for parsing namespace in xml outputs #65
        * XML errors from NCBI are now handled more gracefully #69
        * Documentation and dependency updates
        
        
        *******************
        0.11.0 (09-04-2020)
        *******************
        * `pysradb download` now supports multiple threads for paralle downloads
        * `pysradb download` also supports ultra fast downloads of FASTQs from ENA using aspera-client
        
        
        
        *******************
        0.10.3 (03-26-2020)
        *******************
        * Added test cases for SRAweb
        * API limit exceeding errors are automagically handled
        * Bug fixes for GSE <=> SRR
        * Bug fix for metadata - supports multiple SRPs
        
        Contributors
        
        * Dibya Gautam
        * Marius van den Beek
        
        *******************
        0.10.2 (02-05-2020)
        *******************
        
        * Bug fix: Handle API-rate limit exceeding => Retries
        * Enhancement: 'Alternatives' URLs are now part of `--detailed`
        
        *******************
        0.10.1 (02-04-2020)
        *******************
        
        * Bug fix: Handle Python3.6 for capture_output in subprocess.run
        
        *******************
        0.10.0 (01-31-2020)
        *******************
        
        * All the subcommands (srx-to-srr, srx-to-srs) will now print additional columns where the first two columns represent the relevant conversion
        * Fixed a bug where for fetching entries with single efetch record
        
        *******************
        0.9.9 (01-15-2020)
        *******************
        
        * Major fix: some SRRs would go missing as the experiment dict was being created only once per SRR (See #15)
        * Features: More detailed metadata by default in the SRAweb mode
        * See notebook: https://colab.research.google.com/drive/1C60V-
        
        ******************
        0.9.7 (01-20-2020)
        ******************
        
        * Feature: instrument, run size and total spots are now printed in the metadata by default (SRAweb mode only)
        * Issue: Fixed an issue with srapath failing on SRP. srapath is now run on individual SRRs.
        
        ******************
        0.9.6 (07-20-2019)
        ******************
        
        * Introduced `SRAweb` to perform queries over the web if the SQLite is missing or does not contain the relevant record.
        
        ******************
        0.9.0 (02-27-2019)
        ******************
        
        Others
        ======
        
        * This release completely changes the command line interface replacing click with argparse (https://github.com/saketkc/pysradb/pull/3)
        * Removed Python 2 comptaible stale code
        
        *******************
        0.8.0 (02-26-2019)
        *******************
        
        New methods/functionality
        =========================
        * `srr-to-gsm`: convert SRR to GSM
        * SRAmetadb.sqlite.gz file is deleted by default after extraction
        * When SRAmetadb is not found a confirmation is seeked before downloading
        * Confirmation option before SRA downloads
        
        Bugfix
        ======
        * download() works with wget
        
        Others
        ======
        
        * `--out_dir` is now `out-dir`
        
        
        *******************
        0.7.1 (02-18-2019)
        *******************
        
        Important: Python2 is no longer supported.
        Please consider moving to Python3.
        
        Bugfix
        ======
        
        * Included docs in the index whihch were missed
          out in the previous release
        
        
        *******************
        0.7.0 (02-08-2019)
        *******************
        
        New methods/functionality
        =========================
        * `gsm-to-srr`: convert GSM to SRR
        * `gsm-to-srx`: convert GSM to SRX
        * `gsm-to-gse`: convert GSM to GSE
        
        
        Renamed methods
        ===============
        
        The following commad line options have been renamed
        and the changes are not compatible with 0.6.0
        release:
        
        * `sra-metadata` -> `metadata`.
        * `sra-search` -> `search`.
        * `srametadb` -> `metadb`.
        
        
        
        *******************
        0.6.0 (12-25-2018)
        *******************
        
        Bugfix
        ======
        
        * Fixed bugs introduced in 0.5.0 with API changes where
          multiple redundant columns were output in `sra-metadata`
        
        
        New methods/functionality
        =========================
        * `download` now allows piped inputs
        
        
        
        
        *******************
        0.5.0 (12-24-2018)
        *******************
        
        New methods/functionality
        =========================
        * Support for filtering by SRX Id for SRA downloads.
        * `srr_to_srx`: Convert SRR to SRX/SRP
        * `srp_to_srx`: Convert SRP to SRX
        * Stripped down `sra-metadata` to give minimal information
        * Added `--assay`, `--desc`, `--detailed` flag for `sra-metadata`
        * Improved table printing on terminal
        
        
        *******************
        0.4.2 (12-16-2018)
        *******************
        
        Bugfix
        ======
        
        * Fixed unicode error in tests for Python2
        
        
        *******************
        0.4.0 (12-12-2018)
        *******************
        
        New methods/functionality
        =========================
        
        * Added a new `BASEdb` class to handle common database connections
        * Initial support for GEOmetadb through GEOdb class
        * Initial support or a command line interface:
          - download      Download SRA project (SRPnnnn)
          - gse-metadata  Fetch metadata for GEO ID (GSEnnnn)
          - gse-to-gsm    Get GSM(s) for GSE
          - gsm-metadata  Fetch metadata for GSM ID (GSMnnnn)
          - sra-metadata  Fetch metadata for SRA project (SRPnnnn)
        * Added three separate notebooks for SRAdb, GEOdb, CLI usage
        
        *******************
        0.3.0 (12-05-2018)
        *******************
        
        New methods/functionality
        =========================
        
        * `sample_attribute` and `experiment_attribute` are now included by default in the df returned by `sra_metadata()`
        * `expand_sample_attribute_columns: expand metadata dataframe based on attributes in `sample_attribute` column
        *  New methods to guess cell/tissue/strain: `guess_cell_type()`/`guess_tissue_type()`/`guess_strain_type()`
        *  Improved README and usage instructions
        
        
        *******************
        0.2.2 (12-03-2018)
        *******************
        
        New methods/functionality
        =========================
        
        * `search_sra()` allows full text search on SRA metadata.
        
        
        *******************
        0.2.0 (12-03-2018)
        *******************
        
        Renamed methods
        ===============
        
        The following methods have been renamed
        and the changes are not compatible with 0.1.0
        release:
        
        * `get_query()` -> `query()`.
        * `sra_convert()` -> `sra_metadata()`.
        * `get_table_counts()` -> `all_row_counts()`.
        
        
        New methods/functionality
        =========================
        
        * `download_sradb_file()` makes fetching `SRAmetadb.sqlite` file easy; wget is no longer
          required.
        * `ftp` protocol is now supported besides `fsp` and hence `aspera-client` is now optional.
          We however, strongly recommend `aspera-client` for faster downloads.
        
        Bug fixes
        =========
        * Silenced `SettingWithCopyWarning` by excplicitly doing operations on a copy of
          the dataframe instead of the original.
        
        Besides these, all methods now follow a `numpydoc` compatible documentation.
        
        
        ******************
        0.1.0 (12-01-2018)
        ******************
        
        * First release on PyPI.
        
Keywords: pysradb
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.7
