BED - Biological Entity Dictionary (BED)

An interface for the 'Neo4j' database providing mapping between different identifiers of biological entities. This Biological Entity Dictionary (BED) has been developed to address three main challenges. The first one is related to the completeness of identifier mappings. Indeed, direct mapping information provided by the different systems are not always complete and can be enriched by mappings provided by other resources. More interestingly, direct mappings not identified by any of these resources can be indirectly inferred by using mappings to a third reference. For example, many human Ensembl gene ID are not directly mapped to any Entrez gene ID but such mappings can be inferred using respective mappings to HGNC ID. The second challenge is related to the mapping of deprecated identifiers. Indeed, entity identifiers can change from one resource release to another. The identifier history is provided by some resources, such as Ensembl or the NCBI, but it is generally not used by mapping tools. The third challenge is related to the automation of the mapping process according to the relationships between the biological entities of interest. Indeed, mapping between gene and protein ID scopes should not be done the same way than between two scopes regarding gene ID. Also, converting identifiers from different organisms should be possible using gene orthologs information. The method has been published by Godard and van Eyll (2018) <doi:10.12688/f1000research.13925.3>.

Last updated 12 days ago

7.02 score 8 stars 26 scripts 352 downloads

ReDaMoR - Relational Data Modeler

The aim of this package is to manipulate relational data models in R. It provides functions to create, modify and export data models in json format. It also allows importing models created with 'MySQL Workbench' (<https://www.mysql.com/products/workbench/>). These functions are accessible through a graphical user interface made with 'shiny'. Constraints such as types, keys, uniqueness and mandatory fields are automatically checked and corrected when editing a model. Finally, real data can be confronted to a model to check their compatibility.

Last updated 3 months ago

6.21 score 18 stars 1 packages 15 scripts 257 downloads

bscui - Build SVG Custom User Interface

Render SVG as interactive figures to display contextual information, with selectable and clickable user interface elements. These figures can be seamlessly integrated into 'rmarkdown' and 'Quarto' documents, as well as 'shiny' applications, allowing manipulation of elements and reporting actions performed on them. Additional features include pan, zoom in/out functionality, and the ability to export the figures in SVG or PNG formats.

Last updated 3 months ago

6.13 score 11 stars 19 scripts 161 downloads

TKCat - Tailored Knowledge Catalog

Facilitate the management of data from knowledge resources that are frequently used alone or together in research environments. In 'TKCat', knowledge resources are manipulated as modeled database (MDB) objects. These objects provide access to the data tables along with a general description of the resource and a detail data model documenting the tables, their fields and their relationships. These MDBs are then gathered in catalogs that can be easily explored an shared. Finally, 'TKCat' provides tools to easily subset, filter and combine MDBs and create new catalogs suited for specific needs.

Last updated 3 months ago

6.08 score 5 stars 27 scripts 205 downloads

ClickHouseHTTP - A Simple HTTP Database Interface to 'ClickHouse'

'ClickHouse' (<https://clickhouse.com/>) is an open-source, high performance columnar OLAP (online analytical processing of queries) database management system for real-time analytics using SQL. This 'DBI' backend relies on the 'ClickHouse' HTTP interface and support HTTPS protocol.

Last updated 3 months ago

4.60 score 11 stars 1 packages 12 scripts 400 downloads

neo2R - Neo4j to R

The aim of neo2R is to provide simple and low level connectors for querying neo4j graph databases (<https://neo4j.com/>). The objects returned by the query functions are either lists or data.frames with very little post-processing. It allows fast processing of queries returning many records. And it let the users handle post-processing according to the data model and their needs.

Last updated 3 months ago

4.43 score 9 stars 1 packages 6 scripts 257 downloads