References Variant
Curation of Variant — listings under the References tab.
Summary Table
Click a column header to sort the table.
| NAME | CATEGORY | Main citation | YEAR |
|---|---|---|---|
| Chinese Millionome Database | Variant | NA |
NA |
| Ensembl | Variant | NA |
NA |
| GWAS Catalog | Variant | NA |
NA |
| Open Target Genetics | Variant | NA |
NA |
| PGG.Han 2.0 | Variant | NA |
NA |
| ProtVar | Variant | Stephenson JD et al., Nucleic Acids Res, 2024 |
2024 |
| Taiwan View | Variant | NA |
NA |
| Westlake BioBank for Chinese (WBBC) | Variant | NA |
NA |
| dbSNP | Variant | NA |
NA |
| gnomAD | Variant | NA |
NA |
| jMorp | Variant | Tadaka S et al., Nucleic Acids Res, 2024 |
2024 |
Variant
Chinese Millionome Database (CMDB)
Ensembl
GWAS Catalog
Open Target Genetics
PGG.Han 2.0 (PGG.Han)
ProtVar
PUBMED_LINK
URL
TITLE
ProtVar: mapping and contextualizing human missense variation.
Main citation
Stephenson JD, Totoo P, Burke DF, Jänes J, ...&, Martin MJ. (2024) ProtVar: mapping and contextualizing human missense variation. Nucleic Acids Res, 52 (W1) W140-W147. doi:10.1093/nar/gkae413. PMID 38769064
ABSTRACT
Genomic variation can impact normal biological function in complex ways and so understanding variant effects requires a broad range of data to be coherently assimilated. Whilst the volume of human variant data and relevant annotations has increased, the corresponding increase in the breadth of participating fields, standards and versioning mean that moving between genomic, coding, protein and structure positions is increasingly complex. In turn this makes investigating variants in diverse formats and assimilating annotations from different resources challenging. ProtVar addresses these issues to facilitate the contextualization and interpretation of human missense variation with unparalleled flexibility and ease of accessibility for use by the broadest range of researchers. By precalculating all possible variants in the human proteome it offers near instantaneous mapping between all relevant data types. It also combines data and analyses from a plethora of resources to bring together genomic, protein sequence and function annotations as well as structural insights and predictions to better understand the likely effect of missense variation in humans. It is offered as an intuitive web server https://www.ebi.ac.uk/protvar where data can be explored and downloaded, and can be accessed programmatically via an API.
DOI
10.1093/nar/gkae413
Taiwan View
Westlake BioBank for Chinese (WBBC) (WBBC)
dbSNP
gnomAD
jMorp
PUBMED_LINK
FULL NAME
Japanese Multi-Omics Reference Panel
URL
TITLE
jMorp: Japanese Multi-Omics Reference Panel update report 2023.
Main citation
Tadaka S, Kawashima J, Hishinuma E, Saito S, ...&, Kinoshita K. (2024) jMorp: Japanese Multi-Omics Reference Panel update report 2023. Nucleic Acids Res, 52 (D1) D622-D632. doi:10.1093/nar/gkad978. PMID 37930845
ABSTRACT
Modern medicine is increasingly focused on personalized medicine, and multi-omics data is crucial in understanding biological phenomena and disease mechanisms. Each ethnic group has its unique genetic background with specific genomic variations influencing disease risk and drug response. Therefore, multi-omics data from specific ethnic populations are essential for the effective implementation of personalized medicine. Various prospective cohort studies, such as the UK Biobank, All of Us and Lifelines, have been conducted worldwide. The Tohoku Medical Megabank project was initiated after the Great East Japan Earthquake in 2011. It collects biological specimens and conducts genome and omics analyses to build a basis for personalized medicine. Summary statistical data from these analyses are available in the jMorp web database (https://jmorp.megabank.tohoku.ac.jp), which provides a multidimensional approach to the diversity of the Japanese population. jMorp was launched in 2015 as a public database for plasma metabolome and proteome analyses and has been continuously updated. The current update will significantly expand the scale of the data (metabolome, genome, transcriptome, and metagenome). In addition, the user interface and backend server implementations were rewritten to improve the connectivity between the items stored in jMorp. This paper provides an overview of the new version of the jMorp.
DOI
10.1093/nar/gkad978