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. A ready to use database is provided as a 'Docker' image < https://hub.docker.com/r/patzaw/bed-ucb-human/>. The method has been published by Godard and van Eyll (2018) .


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Reference manual

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install.packages("BED")

1.4.4 by Patrice Godard, a month ago


https://github.com/patzaw/BED


Report a bug at https://github.com/patzaw/BED/issues


Browse source code at https://github.com/cran/BED


Authors: Patrice Godard [aut, cre, cph]


Documentation:   PDF Manual  


GPL-3 license


Imports dplyr, readr, stringr, utils, shiny, DT, htmltools, miniUI, rstudioapi

Depends on neo2R, visNetwork

Suggests knitr, rmarkdown, biomaRt, GEOquery, base64enc, webshot


See at CRAN