ENASearch is a Python library for interacting with ENA's API.
The European Nucleotide Archive (ENA) is a database with a comprehensive record of nucleotide sequencing information (raw sequencing data, sequence assembly information and functional annotation). The data contained in ENA can be accessed manually or programmatically via REST URLs. However, building HTTP-based REST requests is not always straightforward - a user friendly, high-level access is needed to make it easier to interact with ENA programmatically.
We developed ENASearch, a Python library to search and retrieve data from ENA database. It also allows for rich querying support by accessing different fields, filters or functions offered by ENA. ENASearch can be used as a Python package, through a command-line interface or inside Galaxy.
ENASearch can be used via command-line:
$ enasearch --help Usage: enasearch [OPTIONS] COMMAND [ARGS]... The Python library for interacting with ENA's API Options: --version Show the version and exit. -h, --help Show this message and exit. Commands: get_analysis_fields Get the fields extractable for an analysis. get_display_options Get the list of possible formats to display... get_download_options Get the options for download of data from... get_filter_fields Get the filter fields of a result to build a... get_filter_types Return the filters usable for the different... get_results Get the possible results (type of data). get_returnable_fields Get the fields extractable for a result. get_run_fields Get the fields extractable for a run. get_sortable_fields Get the fields of a result that can sorted. get_taxonomy_results Get list of taxonomy results. retrieve_analysis_report Retrieve analysis report from ENA. retrieve_data Retrieve ENA data (other than taxon). retrieve_run_report Retrieve run report from ENA. retrieve_taxons Retrieve data from the ENA Taxon Portal. search_data Search data given a query. $ enasearch search_data --help Usage: enasearch search_data [OPTIONS] Search data given a query. This function - Extracts the number of possible results for the query - Extracts the all the results of the query (by potentially running several times the search function) The output can be redirected to a file and directly display to the standard output given the display chosen. Options: --free_text_search Use free text search, otherwise the data warehouse is used --query TEXT Query string, made up of filtering conditions, joined by logical ANDs, ORs and NOTs and bound by double quotes; the filter fields for a query are accessible with get_filter_fields and the type of filters with get_filter_types [required] --result TEXT Id of a result (accessible with get_results) [required] --display TEXT Display option to specify the display format (accessible with get_display_options) [required] --download TEXT Download option to specify that records are to be saved in a file (used with file option, list accessible with get_download_options) --file PATH File to save the content of the search (used with download option) --fields TEXT Fields to return (accessible with get_returnable_fields, used only for report as display value) [multiple or comma-separated] --sortfields TEXT Fields to sort the results (accessible with get_sortable_fields, used only for report as display value) [multiple or comma-separated] --offset INTEGER RANGE First record to get (used only for display different of fasta and fastq --length INTEGER RANGE Number of records to retrieve (used only for display different of fasta and fastq -h, --help Show this message and exit.
It can also be used as a Python library:
>>> import enasearch >>> enasearch.retrieve_data( ids="A00145", display="fasta", download=None, file=None, offset=0, length=100000, subseq_range="3-63", expanded=None, header=None) [SeqRecord(seq=Seq('GAAGGAAGGTCTTCAGAGAACCTAGAGAGCAGGTTCACAGAGTCACCCACCTCA...GCC', SingleLetterAlphabet()), id='ENA|A00145|A00145.1', name='ENA|A00145|A00145.1', description='ENA|A00145|A00145.1 B.taurus BoIFN-alpha A mRNA : Location:3..63', dbxrefs=)]
The information extracted from ENA can be in several formats: HTML, Text, XML, FASTA, FASTQ, ... XML outputs are transformed in a Python dictionary using xmltodict and the FASTA and FASTQ into SeqRecord objects using BioPython.
ENASearch can be installed with pip:
$ pip install enasearch
or with conda:
$ conda install -c bioconda enasearch
ENASearch comes with tests:
$ make test
These tests are automatically run on TravisCI for each Pull Request.
Documentation about ENASearch is available online at http://bebatut.fr/enasearch
To update it:
- Make the changes in src/docs
- Generate the doc with
$ make doc
- Check it by opening the docs/index.html file in a web browser
- Propose the changes via a Pull Request
Generate the data descriptions
To run, ENASearch needs some data from ENA to describe how to query ENA. Currently, such information is manually extracted into CSV files in the data directory. Python objects are generated from these CSV files with
$ python src/serialize_ena_data_descriptors.py