ENCODExplorer: A compilation of metadata from ENCODE

Audrey Lemacon, Charles Joly Beauparlant and Arnaud Droit.

This package and the underlying ENCODExplorer code are distributed under the Artistic license 2.0. You are free to use and redistribute this software.

“The ENCODE (Encyclopedia of DNA Elements) Consortium is an international collaboration of research groups funded by the National Human Genome Research Institute (NHGRI). The goal of ENCODE is to build a comprehensive parts list of functional elements in the human genome, including elements that act at the protein and RNA levels, and regulatory elements that control cells and circumstances in which a gene is active”[source : ENCODE Projet Portal ].

However, data retrieval and downloading can be really time-consuming using the current web portal.

This package has been designed to facilitate data access by compiling the metadata associated with file, experiment and dataset.

We first extract ENCODE schema from its public github repository. Then we identify the main entities and their relationship with each other to rebuild the ENCODE database into an SQLite database. We also developped a function which can extract the essential metadata in a R object to aid data exploration. We implemented time-saving features to select ENCODE files by querying their metadata and download them.

The SQLite database can be regenerated at will to query ENCODE database locally keep it up-to-date.

This vignette will introduce the imputed ENCODE database model.

Loading ENCODExplorer package

suppressMessages(library(ENCODExplorer))

Data preparation

To generate the SQL database from ENCODE:

# the path (relative or absolute) to the future database
database_filename = "encode.sqlite"
tables = prepare_ENCODEdb(database_filename)

The process can take a few minutes.

Schema

imputed model of the ENCODE database

The edges indicate relationship between two tables : an origin and a destination. The relation is made between a column of the origin table and the id of the destination table.

Those relations are described in the following table:

Relations table

origin destination origin column
access_key user user
analysis_step analysis_step parents
analysis_step document documents
analysis_step_run analysis_step analysis_step
analysis_step_run workflow_run workflow_run
analysis_step software_version software_versions
antibody_approval antibody_characterization characterizations
antibody_approval antibody_lot antibody
antibody_approval target target
antibody_characterization antibody_lot characterizes
antibody_characterization target target
antibody_characterization user reviewed_by
antibody_lot organism host_organism
antibody_lot target targets
award user pi
biosample biosample derived_from
biosample biosample part_of
biosample biosample pooled_from
biosample_characterization biosample characterizes
biosample construct constructs
biosample document protocol_documents
biosample donor donor
biosample organism organism
biosample rnai rnais
biosample talen talens
biosample treatment treatments
characterization document documents
construct_characterization construct characterizes
construct document documents
construct target promoter_used
construct target target
dataset document documents
dataset file related_files
donor_characterization donor characterizes
donor organism organism
experiment experiment possible_controls
experiment target target
file analysis_step_run step_run
file dataset dataset
file experiment dataset
file file controlled_by
file file derived_from
file file paired_with
file file supercedes
file platform platform
file replicate replicate
fly_donor document documents
human_donor human_donor children
human_donor human_donor fraternal_twin
human_donor human_donor identical_twin
human_donor human_donor parents
human_donor human_donor siblings
lab award awards
lab user pi
library biosample biosample
library dataset spikeins_used
library document documents
library treatment treatments
mouse_donor mouse_donor littermates
page page parent
pipeline analysis_step analysis_steps
pipeline analysis_step end_points
pipeline document documents
publication dataset datasets
quality_metric analysis_step_run step_run
quality_metric file files
replicate antibody_lot antibody
replicate experiment experiment
replicate library library
replicate platform platform
rnai_characterization rnai characterizes
rnai document documents
rnai target target
software publication references
software_version software software
talen document documents
target organism organism
treatment document protocols
treatment lab lab
user lab lab
user lab submits_for
workflow_run file input_files
workflow_run pipeline pipeline
workflow_run software_version software_version
worm_donor document documents
worm_donor worm_donor outcrossed_strain

For example: [file —> replicate —> replicate] enables to write the following relation in a SQL query : file.replicate = replicate.id.