Search Help
GDRD provide two search manners for users, ‘Global Search’ and ‘Local Search’. Global Search makes the user get all possible result of a corresponding query, various form of query supported in global search. The user can access home page search box to perform a global search, the more exact result can get by performing local search in particular area of a page. As fuzzy search is the default search method on our website, anything input will get a possible result, the more meaningful the input, the more useful it returns, we recommend user use appropriate words as a query during searching.
GDRD supports the search for the variant, gene, disease, phenotype respectively; variant search is our main feature. As causative mutation reported in the paper usually provides cDNA change or amino acid change, instead chromosome coordinate; to get variant information without chromosome coordinate is an indeed demand. We try to fullfile this need by provide rich-annotated information and fuzzy search feature; the user can search by chromosome coordinate or rs id directly, or search by HGVSc, HGVSp, Abbr amino acid change and sequence context search on ‘Local Search’.
For example, different substitutions of the Lys650 residue of the FGFR3 gene are associated with a wide range of clinical phenotypes. To get detail information on those variants without chromosome coordinate or rs id, you can use ‘FGFR3’ as a query to perform a global search first and then use ‘Lys650’ as a query to perform a local search on the variant result page.
Page help
Variant detail page > Population data
Based on "Standards and guidelines for the interpretation of sequence variants [ACMG2015]", we organized population data in this panel, provide 'Population Allele Frequence Information', 'Population Genotype Information', and 'Case-control Study Information', user can use those information to make a evaluation on 'Bengin/Pathogenic' of a variant, 5 evidence tags can be draw concluded here, they are defined as below:
- BA1: Allele frequency in a control population greater than 5%;
- BS1: MAF is too high(greater than expected) for disorder;
- BS2: Observation in controls inconsistent with disease penetrance;
- PM2: Absent in population databases;
- PS4: Prevalence in affecteds statistically increased over controls;
Feel free to contact us if you have any suggestions, questions or issue.
Data source of this panel:
| Data source | Latest version | Used version | Data source description |
|---|---|---|---|
| dbNSFP | v3.5a 20180112 | v3.5a 20170806 | dbNSFP is a database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. |
| 1000Genomes | phase3 20130502 | phase3 20130502 | The goal of the 1000 Genomes Project was to find most genetic variants with frequencies of at least 1% in the populations studied. The final data set contains data for 2,504 individuals from 26 populations. Low coverage and exome sequence data are present for all of these individuals, 24 individuals were also sequenced to high coverage for validation purposes. |
| ESP | EVS-v.0.0.30 20141103 | EVS-v.0.0.30 20141103 | The goal of the NHLBI GO Exome Sequencing Project (ESP) is to discover novel genes and mechanisms contributing to heart, lung and blood disorders by pioneering the application of next-generation sequencing of the protein coding regions of the human genome across diverse, richly-phenotyped populations and to share these datasets and findings with the scientific community to extend and enrich the diagnosis, management and treatment of heart, lung and blood disorders. The current EVS data release (ESP6500SI-V2) is taken from 6503 samples drawn from multiple ESP cohorts and represents all of the ESP exome variant data. |
| STSI | v0.1 20170818 | v0.1 20160530 | Wellderly Study pursued genome sequencing of a cohort of individuals who are >80 years old with no chronic diseases to understand the genetics of disease-free aging without medical intervention. |
| GWAS Cateloge | v1.0 20180116 | v1.0 20171120 | The GWAS Catalog provides a consistent, searchable, visualisable and freely available database of published SNP-trait associations, which can be easily integrated with other resources, and is accessed by scientists, clinicians and other users worldwide. |
Variant detail page > Computational and predictive data
Based on "Standards and guidelines for the interpretation of sequence variants [ACMG2015]", we organized 'Computational and predictive data' in this panel, provide 'Gene Level Information' and 'Variant level information', user can use those information to make a evaluation on 'Bengin/Pathogenic' of a variant, 10 evidence tags can be draw concluded here, they are defined as below:
- BP1: Missense in gene where only truncating cause disease
- BP3: In-frame indels in repeat without known function
- BP4: Multiple lines of computational evidence suggest no impact on gene/gene product
- BP7: Silent variant with non predicted splice impact
- PP3: Multiple lines of computational evidence support a deleterious effect on the gene/gene product
- PM5: Novel missense change at an amino acid residue where a different pathogenic missense change has been seen before
- PM4: Protein length changing variant
- PS1: Same amino acid change as an established pathogenic variant
- PVS1: Predicted null variant in gene where LOF is a known mechanism of disease
- PP2: Many genes have a defined spectrum of pathogenic and benign variation
Feel free to contact us if you have any suggestions, questions or issue.
Data source of this panel:
| Data source | Latest version | Used version | Data source description |
|---|---|---|---|
| dbNSFP | v3.5a 20180112 | v3.5a 20170806 | dbNSFP is a database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. |
| DOMINO | v1 20170403 | v1 20170403 | DOMINO is a tool assessing the likelihood for a gene to harbor dominant changes. It’s a robust and reliable tool that can infer dominance of candidate genes with high sensitivity and specificity, making it a useful complement to any NGS pipeline dealing with the analysis of the morbid human genome. |
| GDI | GDI_full 20151028 | GDI_full 20151028 | The gene damage index (GDI) is the accumulated mutational damage of each human gene in healthy human population, based on the 1000 Genomes Project database (Phase 3) gene variations of healthy individuals and of the CADD score for calculating impact. We have shown that highly damaged human genes are unlikely to be disease-causing. GDI is very effective to filter out variants harbored in highly damaged (high GDI) genes that are unlikely to be disease-causing. |
Variant detail page > Individual data
Based on "Standards and guidelines for the interpretation of sequence variants [ACMG2015]", we organized 'Individual data' in this panel, provide indidual genotype and phenotype information, The user can evaluate 'Bengin/Pathogenic' of a variant based on the information presented here, 1 evidence tag can be draw concluded, it is defined as below:
- BP5: Found in case with an alternate cause
Feel free to contact us if you have any suggestions, questions or issue.
Variant detail page > Other database
Based on "Standards and guidelines for the interpretation of sequence variants [ACMG2015]", we organized 'Other database' in this panel, such as ClinVar, The user can evaluate 'Bengin/Pathogenic' of a variant based on the information presented here, 2 evidence tags can be draw concluded, they are defined as below:
- BP6: Reputable source w/out shared data support benign
- PP5: Reputable source support pathogenic
Feel free to contact us if you have any suggestions, questions or issue.
Data source of this panel:
| Data source | Latest version | Used version | Data source description |
|---|---|---|---|
| ClinVar | 20180104 | 20171030 | ClinVar aggregates information about genomic variation and its relationship to human health. |