GenDaB

GenDaB - the Gene DataBase

GenDaB is a one-stop-shop for human genes. The database includes a plethora of data and provides many search options. Genes can be specified by their gene symbol or NCBI ID but also indirectly, using their position, the phenotypes they may cause or their protein-protein interactions (to name a few options). The database can also be queried using an API which makes it easy to integrate information from GenDaB in your own applications (examples on the left.)
GenDaB is free to use and it does not require any registration.

GenDaB Documentation

Query mask

The query mask is the main page and search interface of GenDaB. It offers a multitude of query options, which are sorted into different sections and can be expanded and collapsed depending on your research interests.
In addition to the following documentation on those sections, you may also refer to the help option on the query mask itself. To use this help, simply select the Display help checkbox above the first section.
This will activate pop-ups that will display additional information on an input element whenever the mouse pointer is drawn over it.

General settings

At the top of the query mask, there are two basic settings: selecting the genome version for your query (at present GRCh37 or GRCh38) and specifying whether the output is ordered by gene symbol or position. Additionally there is the aforementioned Display help checkbox and a Reset this page option, which will delete all your individual input and reset the query mask to default status.

Display options

As the name suggests, in this sections you can choose which data sources to display in the output. Carefully selecting these options can help to keep the size of the output in check.
Note that these are not the only data sources GenDaB can display. For a list of all integrated data sources see Integrated data.

Additionally, there are radio buttons in other sections to hide, show or filter by other data sources in their respective sections. To hide, show or filter by these, select the respective radio button in the relevant areas explained below.

Set cookies

Above the Search button which will submit your query, you have the option to store your selection in the Display Options section in cookies, so that the query mask will remember your preferred settings when you return to it at a later time. Please note, that your setting will only be saved if you select this option and then submit your query with the Searchbutton. Checking this box without submitting your query will not save your selection.

Candidate genes, regions or panels

To query GenDaB, candidate genes must be defined. This can be done in several ways.

Single genes / gene lists

If you already have specific genes in mind, the simplest option is to directly specify genes to be treated as candidates. Simply insert a single or comma-separated list of HGNC gene symbols, Ensembl IDs or NCBI gene IDs.

Regions from BED files

Another option is to specify genetic regions of interest in bed file format, SNP to SNP or gene to gene.

Example:

1 10000 200000
1:10000-200000
rs564271862-rs1769661
NOTCH2-ITGA10

This can be done via manual input or by uploading a .bed file. Example: brca_example.bed

Gene Type

You may want to restrict the output to a specific gene type, which can easily be done by selecting it in the Gene type drop down. By default this option is set to all and does not restrict the output based on types of genes.

Mitochondrial proteins

You may restrict your search to genes with strong support of mitochondrial localisation as reported by MitoCarta 3 by selecting the checkbox Limit to mitochondrial proteins.

Panels

In this section you can choose which Common Gene Panels to display or filter by, by using the corresponding radio button and selecting panels such as HPO and ACMG with their respective checkboxes. For the Genomics England PanelApp, you can search for and select individual panels, which are sorted by disease categories that can be expanded and collapsed. To search for a specific panel by name, you may use the search field above the PanelApp list. Please note that for the search to work, you must put in at least four letters of the panel you seek.

Phenotypes

When searching for candidates genes, it is likely that you may want to look for genes causing specific phenotypes. GenDaB offers multiple options to display and filter for known phenotypes based on several ontologies such as the Human Phenotype Ontology (HPO) and OMIM.

Search for these keywords (OMIM / GeneRIFs)

Type in comma-separated keywords to search for in OMIM reports and GeneRIFs to be highlighted in the output. You may also upload a GA4GH Phenopacket.
Example: HPO_ORPHA_OMIM.json.
Use the radio buttons to either show or filter the output to genes with at least one of these words in their reports.

Search for these human phenotypes

When looking for genes linked to specific diseases, displaying and filtering for phenotypes may be helpful. In GenDaB we store human disease descriptions from OMIM and Orphanet, as well as clinical signs and symptoms in humans provided by the Human Phenotype Ontology (HPO). Genes are linked to OMIM disease descriptions and/or HPO terms using data from NCBI MedGen. By selecting IDs or terms from OMIM, Orphanet and/or HPO, you can further refine your search. First select with the radio buttons whether to hide, show or filter the results for each ontology. If you want to filter the genes by human phenotypes, you may either search and select terms or put in IDs directly. IDs need to adhere to the following format:

Example:

HP:123
ORPHA:456
OMIM:789

To search for HPO, Orphanet and OMIM terms, first choose in which data sources to look for with the checkboxes. Then enter at least four letters into the field Enter phenotypes here to look for the search term. A list will open containing IDs with descriptions matching the search term. Choose from the list by clicking on a term.

Search for these broad mouse phenotypes

Select one or more mouse phenotypes to filter your search. To select multiple options, press CTRL while clicking on terms.

Function

When looking for candidate genes, you may also be interested in information provided through Gene Ontology, Reactome and WikiPathways. These data sources are utilized in the Function section of the query mask. Use the radio buttons to select whether to hide, show or filter the results using Gene Ontology, Reactome and/or WikiPathways. If you want to filter the genes by one of these, you may either search and select terms or put in IDs directly. IDs need to adhere to the following format:

Example:

GO:123
Reactome:789
WikiPathways:456

To search for Gene Ontology, Reactome and WikiPathways terms, first choose in which data sources to look for your search term with the checkboxes. Then enter at least four letters into the field Enter gene function here to look for the search term. A list will open containing IDs with descriptions matching the search term. Choose from the list by clicking on a term.

Interactions

Protein-protein interactions (PPIs) are a key element in the understanding of cellular processes. GenDaB enables the user to search for genes encoding proteins that interact with the encoded proteins of your candidate genes by using annotations provided by the STRING database. The radio button in this section allows the user to choose whether to hide or show such interaction annotations in the output.
Additionally, when setting the radio button to filter, the output can be restricted to candidate genes whose proteins are known to interact with proteins specified by the user. The genes of interest must be entered into the text area as a comma-separated list of NCBI gene IDs or HGNC gene symbols.

Expression

You may be interested to see which organs or tissues your candidate genes are expressed in. This selection allows you to customize the expression output according to your areas of interest. First select with the radio buttons whether to hide, show or filter the results. If you expect your candidate gene to be expressed in a certain organ, system or tissue, you may filter your output by selecting one of the options here. In addition, you can select the developmental stage as well as the experimental method you're interested in. Please note that for expression, GenDaB filters out only those genes which, according to our data, are explicitly not expressed in a certain tissues. Genes for which there is no data indicating that they are expressed or not expressed in the selected tissues, will still be included in the output.

Cellular localisation

When searching for genes of interest, it is often helpful to restrict the search to genes whose gene products are found in certain cellular compartments. This can be done by selecting the respective checkboxes in the Cellular localisation section. Since these terms are based on the Gene Ontology, they are organized in a hierarchical structure. Thus, selecting a term will also select all its sub-terms. However, to enable a more fine-grained control, GenDaB offers the possibility to select only a subset of the sub-terms. To do so, expand the parent terms to show all their sub-terms and select the terms of interest.
Now only genes that are annotated with the selected terms will be displayed in the output, when the radio button is set to filter.


Output

Once you are finished with your input and selections on the query mask and send your query by pressing the Search button, you will be forwarded to the output/result page. This page will supply you with rich information on the candidate genes that fit all your input parameters.

General overview

When the output page opens, you will be presented with a list of genes, which can be collapsed and expanded by either clicking on the individual bar of a single gene or using the Expand all genes button. The collapsed genes will only display the gene symbol, name and, if selected and applicable, a flag for ACMG actionable genes.

On top of the page, the number of genes found through your query will be displayed, along with the following options:

Below the list of genes, a list of our data sources is provided along with the date they were last updated in GenDaB.

Gene specific information

Once you expand a gene, a lot of information on this gene will be on display. Some of this data is shown by default, some will only be shown when it is selected via the display option or show/filter radio buttons (see section Display options in Query mask). Sections, where the provided information is very long will be collapsed within the gene and can be expanded using the and collapsed again using the icon. Scroll bars next to a section further indicate that a section is collapsed and not all information is displayed. The data shown in the result table is entirely configurable in the query mask. The only sections that are always shown no matter the selections are the gene symbol, name and type in the gene's expandable tab, as well as basic information in the first expanded line such as chromosome, positions and genome version.
All other information can be configured. Some sections will be shown by default and can be hidden and some will be hidden by default and can be set to show on the query mask.

Section overview

Section Shown by default Description
Links yes Provides a number of link outs to NCBI, ENSEMBL, GeneCards and PubMed for further information on the gene. Each of these link outs can be individually hidden or shown via the display options on the query mask.
UniProt yes Provides link outs to proteins associated with the gene found in UniProt.
Paralogs yes Lists genes with protein paralogs for the queried gene and links to the GenDaB output for those genes.
InterPro domains yes Lists and links out to protein domains found via InterPro.
PFAM yes Lists and links out to protein families found via PFAM (now integrated in InterPro).
WikiPathways yes Lists and links to pathways associated with the queried gene found through WikiPathways.
Reactome pathways yes Lists and links to pathways associated with the queried gene found through Reactome.
HPO yes Lists and links to associated clinical signs and symptoms in the Human Phenotype Ontology. Genes and HPO terms are linked using data from NCBI MedGen.
Orphanet yes Lists and links to associated disease descriptions in Orphanet and shows additional information such as somatic, germline, candidate gene tested, loss/gain of function etc. in colour-coded labels for each phenotype when applicable.
OMIM yes Provides comprehensive phenotype reports as found in OMIM. Unlike other sections, each associated OMIM entry is collapsed in its own section. Additionally, when a specific phenotype has only been confirmed in mice, this will be indicated by a highlighted "only shown in mice" text. Genes and disease descriptions are linked using data from NCBI MedGen.
OMIM gene info yes Shows the gene specific OMIM report for the queried gene.
Transcript summary yes An overview of how many transcripts of each category (such as protein-coding or retained intron) are available for the queried gene. By clicking on Show transcripts beneath the "Transcript summary" heading, the full list of relevant transcripts can be displayed. Similarly, clicking on Hide transcripts will return you to the Transcript summary view.
Panels no Lists and links to those panels selected on the query mask. When no specific panels are selected but the display option is set to show, all panels including Genomics England panels will be displayed.
GeneRIFs yes A list of functional annotations provided through GeneRIF.
Gene Ontology yes Lists and links to associated entries in the Gene Ontology. These are divided into three categories as indicated by their headings: localisation, process and function.
MPO yes Lists and links to associated entries in the Mammalian Phenotype Ontology.
Interactions no Lists a number of known interaction partners found via STRING. Each protein-coding gene listed links to the corresponding GenDaB entry. Additionally, the score and method (such as experimental or text mining) provided by STRING are shown. By clicking on the method, you will be redirected to the associated entry on the STRING website. Genes which were specifically queried in the interactions tab of the query mask will be marked by a bold "queried" text, whereas genes which are also listed as candidate genes in your output are indicated by a bold "In search" text.
Expression no The output here will be largely dependant on your selection in the Expression tab of the query mask. Only expression in user selected tissues and developmental stage and through the chosen experimental method will be shown. Please note that when set to filter, the expression output will show genes which are epressed in at least one of the selected tissues as well as genes for which no expression data in GenDaB is available. Only genes for which our data explicitly indicates that they are not expressed in either of the selected tissues will be filtered out.

For further information on the sources of the shown data, please refer to Integrated data.


Integrated data

GenDaB integrates ~15 external resources, which are updated on a regular basis (last update: 13 August 2023).

Data source Integrated data Reference
NCBI Gene NCBI Gene ID + Synonym, geneRIFs (functional annotation) Sayers EW, Bolton EE, Brister JR, et al. Database resources of the national center for biotechnology information. Nucleic Acids Res. 2022;50(D1):D20-D26. doi:10.1093/nar/gkab1112
Gene Ontology (GO) biological process, cellular component, molecular function Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25(1):25-29. doi:10.1038/75556

Gene Ontology Consortium, Aleksander SA, Balhoff J, et al. The Gene Ontology knowledgebase in 2023. Genetics. 2023;224(1):iyad031. doi:10.1093/genetics/iyad031
MitoCarta 3.0 Mitochondrial gene data, Maestro-Score Rath S, Sharma R, Gupta R, et al. MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations. Nucleic Acids Res. 2021;49(D1):D1541-D1547. doi:10.1093/nar/gkaa1011
ENSEMBL transcript information, paralogs, protein families Cunningham F, Allen JE, Allen J, et al. Ensembl 2022. Nucleic Acids Res. 2022;50(D1):D988-D995. doi:10.1093/nar/gkab1049
Interpro protein domains Paysan-Lafosse T, Blum M, Chuguransky S, et al. InterPro in 2022. Nucleic Acids Res. 2023;51(D1):D418-D427. doi:10.1093/nar/gkac993
PFAM protein domains Mistry J, Chuguransky S, Williams L, et al. Pfam: The protein families database in 2021. Nucleic Acids Res. 2021;49(D1):D412-D419. doi:10.1093/nar/gkaa913
STRING protein interactions Szklarczyk D, Gable AL, Nastou KC, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets [published correction appears in Nucleic Acids Res. 2021 Oct 11;49(18):10800]. Nucleic Acids Res. 2021;49(D1):D605-D612. doi:10.1093/nar/gkaa1074
Reactome biochemical pathways Gillespie M, Jassal B, Stephan R, et al. The reactome pathway knowledgebase 2022. Nucleic Acids Res. 2022;50(D1):D687-D692. doi:10.1093/nar/gkab1028
WikiPathways biochemical pathways Martens M, Ammar A, Riutta A, et al. WikiPathways: connecting communities. Nucleic Acids Res. 2021;49(D1):D613-D621. doi:10.1093/nar/gkaa1024
OMIM phenotype data Amberger JS, Bocchini CA, Scott AF, Hamosh A. OMIM.org: leveraging knowledge across phenotype-gene relationships. Nucleic Acids Res. 2019;47(D1):D1038-D1043. doi:10.1093/nar/gky1151
OrphaNet phenotype data Maiella S, Olry A, Hanauer M, et al. Harmonising phenomics information for a better interoperability in the rare disease field. Eur J Med Genet. 2018;61(11):706-714. doi:10.1016/j.ejmg.2018.01.013
Human Phenotype Ontology (HPO) phenotype data Köhler S, Gargano M, Matentzoglu N, et al. The Human Phenotype Ontology in 2021. Nucleic Acids Res. 2021;49(D1):D1207-D1217. doi:10.1093/nar/gkaa1043
Mouse Genome Database (MGD) homologous mouse genes Blake JA, Baldarelli R, Kadin JA, et al. Mouse Genome Database (MGD): Knowledgebase for mouse-human comparative biology. Nucleic Acids Res. 2021;49(D1):D981-D987. doi:10.1093/nar/gkaa1083
PanelApp gene panels Martin AR, Williams E, Foulger RE, et al. PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Nat Genet. 2019;51(11):1560-1565. doi:10.1038/s41588-019-0528-2
(Modified) Kingsmore Panel gene panels Bell CJ, Dinwiddie DL, Miller NA, et al. Carrier testing for severe childhood recessive diseases by next-generation sequencing. Sci Transl Med. 2011;3(65):65ra4. doi:10.1126/scitranslmed.3001756
Expression Atlas expression Papatheodorou I, Moreno P, Manning J, et al. Expression Atlas update: from tissues to single cells. Nucleic Acids Res. 2020;48(D1):D77-D83. doi:10.1093/nar/gkz947

For suggestions on other data sources we should include please contact: dominik.seelow (at) bih-charite.de

Tutorial

In this simple tutorial, a typical use case for GenDaB is described. For the gene region on chromosome 15, position 74000000-80000000, we look for all interaction partners of the protein p53.

1. Genomic region of interest:
First enter the gene region in the text field in the "candidate genes, regions or panels" tab. candidate genes, regions or panels tab You can also upload a bed file to define regions.

2. Filter for interactions with p53:
To filter for interactions with p53, type the NCBI-ID or gene symbol of the encoding gene TP53 into the text field of the interaction tab and change the setting of the radio buttons to filter (blue). With this setting, only genes encoding proteins that are know to interact with p53 are displayed in the output. candidate genes, regions or panels tab

3. Start the query: Press the submit-button to initiate the query.

4. Result exploration: The result page shows six encoding genes in the genomic regions whose proteins interact with p53, namely PML, CYP1A1, SIN3A, FBXO22, CHRNA3 and CTSH. Information about a particular gene can be retrieved by pressing the tab of the gene. candidate genes, regions or panels tab

Examples

Use case - Progeria

Imagine you have a patient suffering from progeria and find a homozygous deletion on chromosome 1 between 155 and 159 Mbp. You know from electron microscopy that the nuclei are not in good shape. You search for genes which
1.) are located within the deletion
2.) cause a murine ageing phenotype
3.) have a gene product located in the nuclear membrane.

See example as Input in query mask or Output.

Step 1:

Step 2:

Step 3:


Simple query examples

In addition to the use case, below we provide a few simple examples on how to use GenDaB for different search goals. Clicking on the Input in query mask will lead you to a pre-filled query mask where you can adjust the settings, whereas clicking on Output will lead you directly to the results.

Example 1

Filter for the keyword "muscular" in the genes LBR, LMNA and FBN1.
See example as Input in query mask or Output.

Example 2

Look for HPO term Myopathy (HP:3198) in genes ABL1 and ACACA.
See example as Input in query mask or Output.

Example 3

Filter the genes SOS1 and LMNA for the WikiPathways term "Regulation of actin cytoskeleton".
See example as Input in query mask or Output.

API

Our API allows you to retrieve data programmatically, making it easy to integrate our server's resources into your own applications or scripts. Whether you prefer AJAX calls, Python scripting, or using curl commands, we've got you covered.

API parameters

Default values are marked in bold green.

Name Parameter (API) Values Examples Description
JSON Output-Format json 0, 1 json=1 Retrieve the output in JSON format.
Order / Prioritisation order position, genesymbol, matching_score order=genesymbol Order the output specifically by genesymbol or genomic position.
Defining the genes of interest
Genome build genome_version 37, 38 genome_version=38 Genome build to use for the query (GRCh37 or GRCh38).
Gene input: All genesymbol Gene symbols (or gene IDs) genesymbol=APP,351 Enter a comma-separated list of genesymbols (NCBI Gene IDs are also accepted).
Gene input: IDs gene_id NCBI Gene IDs gene_id=351,4000 Enter a comma-separated list of NCBI Gene IDs.
Genomic region(s) beddata BED-file content, marking the region of interest (separated by commas or line-breaks) beddata=17:43044295-43125364 Genomic region(s) of interest.
Protein-coding genes only_proteincoding 0, 1 only_proteincoding=1 Select only protein-coding genes.
Mitochondrial proteins mitochondriome 0, 1 mitochondriome=1 Select only genes of mitochondrial proteins.
Gene panels
Gene Panel(s) show_panels 0, 1, filter show_panels=1, show_panels=filter 1: Show gene panels that include the given gene list.
Filter: Filter genes according to the selected gene panels.
Specific Gene Panel genepanel_ {panel_number} 0, 1 genepanel_265=1 Selection of specific gene panel for filtering of output genes.
Highlighting / Filtering phenotypes
Keywords keywords Words, separated by commas or spaces keywords=dementia Highlight/Filter genes that contain the given keywords in their description (GeneRIFs, OMIM-, and Orphanet-results).
Apply keywords show_keywords 0, 1, filter show_keywords=1, show_keywords=filter 1: Highlight (only in non-JSON output) genes that contain the given keywords in their description (GeneRIFs, OMIM-, and Orphanet-results).
Filter: Filter genes that contain the given keywords in their description (GeneRIFs, OMIM-, and Orphanet-results).
Phenotype phenotype HPO-IDs (e.g. HP:726), OMIM-IDs (e.g. OMIM:607822), Orphanet-IDs (e.g. ORPHA:238616) phenotype=HP:726 Select HPO-, OMIM-, or Orphanet-IDs to highlight/ filter genes that are associated with the given phenotype.
Required: Activate highlighting/ filtering with show_hpo or show_omim or show_orphanet.
HPO show_hpo 0, 1, filter show_hpo=1, show_hpo=filter 1: Highlight (only in non-JSON output) genes that are associated with the given HPO-IDs.
Filter: Filter genes that are associated with the given HPO-IDs.
OMIM show_omim 0, 1, filter show_omim=filter 1: Highlight (only in non-JSON output) genes that are associated with the given OMIM-IDs.
Filter: Filter genes that are associated with the given OMIM-IDs.
Orphanet data show_orphanet 0, 1, filter show_orphanet=filter 1: Highlight (only in non-JSON output) genes that are associated with the given Orphanet-IDs.
Filter: Filter genes that are associated with the given Orphanet-IDs.
MPO / MGD phenotype MGD/MPO-IDs (comma-separated) phenotype=MP:0005386, MP:0002006 Select MPO-IDs to highlight/ filter genes that are associated with the given phenotype.
Apply MPO / MGD phenotypes show_mpo 0, 1, filter show_mpo=1, show_mpo=filter 1: Highlight (only in non-JSON output) genes that are associated with the given MPO-IDs.
Filter: Filter genes that are associated with the given MPO-IDs.
Highlighting / Filtering functional features
Selection: Function function Either GO-IDs (e.g. GO:282), Reactome-IDs (e.g. Reactome:174587), or WikiPathways-IDs (e.g. WikiPathways:2870) function=GO:278, Reactome:174587, WikiPathways:2870 Select GO-, Reactome-, or WikiPathways-IDs to highlight/ filter genes that are associated with the given function.
Wikipathways show_wikipathways 0, 1, filter show_wikipathways=1, show_wikipathways=filter 1: Highlight (only in non-JSON output) genes that are associated with the given WikiPathways-IDs.
Filter: Filter genes that are associated with the given WikiPathways-IDs.
Reactome show_reactome 0, 1, filter show_reactome=1, show_reactome=filter 1: Highlight (only in non-JSON output) genes that are associated with the given Reactome-IDs.
Filter: Filter genes that are associated with the given Reactome-IDs.
Gene Ontology (GO) show_go 0, 1, filter show_go=1, show_go=filter 1: Highlight (only in non-JSON output) genes that are associated with the given GO-IDs.
Filter: Filter genes/proteins that are associated with the given GO-IDs.
Protein-protein interactions
Selection: STRING Interactions interactions NCBI Gene IDs or gene symbols (comma-separated) interactions=4000,4001 Highlight/Filter for protein-protein interaction partners by selecting the gene IDs or gene symbols of the encoding genes.
STRING Interactions show_interactions 0, 1, filter show_interactions=1, show_interactions=filter 1: Highlight (only in non-JSON output) the encoding genes of protein-protein interaction partners.
Filter: Filter encoding genes whose proteins interact with the encoded protein of the given genes.
Expression settings
Expression (Switch) show_expression 0, 1 show_expression=1 Show expression data.
Required: Selection of developmental stage(s), experimental method, and tissue(s).
Expression in adult tissue expression_adult 0, 1 expression_adult=1 Show expression in adult tissues.
Expression in fetal tissue expression_fetal 0, 1 expression_fetal=1 Show expression in fetal tissues.
RNA expression (RNA-seq) expression_rna 0, 1 expression_rna=1 Show RNA expression.
Protein expression expression_protein 0, 1 expression_protein=1 Show protein expression.
RNA expression (RNA-CAGE) expression_cage 0, 1 expression_cage=1 Show expression data from RNA-CAGE experiments.
Expression records for tissue {tissue_name} expression_ {tissue_name} 0, 1 expression_brain=1 Show expression data for the given gene(s)/protein in the selected tissues.
Cellular Localisation
Cellular compartments localisation_{GO-ID} 0, 1 localisation_5886=1 Select only genes with gene products in the given cellular compartment.
Additional resources
Synonyms show_synonyms 0, 1 show_synonyms=1 Show synonyms of the given gene(s).
UniProt show_uniprot 0, 1 show_uniprot=1 Show UniProt data for the given gene(s).
Transcripts show_transcripts 0, 1 show_transcripts=1 Show transcript data for the given gene(s).
GeneRIFs show_generifs 0, 1 show_generifs=1 Show GeneRIFs for the given gene(s).
Interpro show_interpro 0, 1 show_interpro=1 Show Interpro data for the given gene(s).
Pfam show_pfam 0, 1 show_pfam=1 Show Pfam data for the given gene(s).
Paralogs show_paralogs 0, 1 show_paralogs=1 Show paralogs for the given gene(s).

Retrieving data with curl or wget

curl example
curl -d 'genesymbol=APP,APOE,SHOX&json=1' https://www.genecascade.org/gd-cgi/results.cgi
wget example
wget "https://www.genecascade.org/gd-cgi/results.cgi?genesymbol=LBR,LMNA,FBN1&json=1" -O json.json

Retrieving data with Python

import json
import requests

def process_data(obj):
	text = json.dumps(obj, sort_keys=True, indent=4)
	pass # Process your data here

if __name__ == "__main__":
	parameters = {
	"genesymbol": "APP,APOE,SHOX",
	"json": 1
	}

	response = requests.get("https://www.genecascade.org/gd-cgi/results.cgi", params=parameters)
	process_data(response.json())

			
Download example.

Integration via AJAX

GenDaB can be used by your own website to include gene information in various ways. The example below demonstrates how to extract the gene description and chromosome, as well as the start and end position of a gene.
var gene = document.forms[0].genesymbol.value;
var req = new XMLHttpRequest();
req.onreadystatechange = function () {
	if ((req.readyState == 4) && (req.status == 200)) {
	// console.log(req.responseText);
		const results = JSON.parse(req.responseText);
		document.forms[0].description.value = results[0].description;
		document.forms[0].chromosome.value = results[0].chromosome;
		document.forms[0].start.value = results[0].start_pos;
		document.forms[0].end.value = results[0].end_pos;
	}
	else if (req.readyState == 4) {
		alert(req.status)
	}
};
req.open('get', 'https://www.genecascade.org/gd-cgi/results.cgi' + '?json=1&genesymbol=' + gene, true);
req.send();
			
Test working example.

Integration via iFrames

GenDaB supports the integration of its search interface into other web applications via iFrames. This allows for the seamless inclusion of GenDaB into existing information systems. The following code snippet shows how to incorporate the GenDaB search interface into a web application:
<iframe id="tutorial_frame"
src="https://www.genecascade.org/gd-cgi/results.cgi?genesymbol=APOE,APP"
style="position: fixed; top: 0px; bottom: 0px; right: 0px;
width: 100%; border: none; margin: 0; padding: 0;
overflow: hidden; z-index: 999999; height: 100%;">
</iframe>
			
Test working example.

API examples

Below we provide a few simple examples on how to use the GenDaB API for different search goals. Clicking the example links will lead you directly to the result in either JSON or HTML format. For further information on the parameters and how to use them, please refer to the API parameters section.

Example 1

Filter for the keyword "muscular" in OMIM reports for the genes LBR, LMNA and FBN1.
API parameters: genesymbol=LBR,LMNA,FBN1 - keywords=muscular - show_keywords=filter - show_omim=1
See example as JSON or HTML.

Example 2

Look for Myopathy (HPO) in genes ABL1 and ACACA. Also show OMIM and Orphanet for the results.
API parameters: genesymbol=ABL1,ACACA - phenotype=HP:3198 - show_hpo=1 - show_orphanet=1 - show_omim=1
See example as JSON or HTML.

Example 3

Filter the genes SOS1 and LMNA for the WikiPathways term "Regulation of actin cytoskeleton".
API parameters: genesymbol=SOS1,LMNA - function=WikiPathways:51 - show_wikipathways=filter
See example as JSON or HTML.

Frequently Asked Questions

How do I use the hide, show and filter buttons?

These radio buttons can be used to hide or display certain data in the output as well as use them to filter the results. By default, they will be set to either hide or show. When input is detected in a specific section, the corresponding radio button will automatically switch to filter. As the names suggest, the hide and show option decide whether a specific section in the output is shown for each gene. For example setting the Interaction section to show will show all interactions for each gene that we have in our database, whereas setting it to hide will cause the output to not display any interaction data at all. However, setting a section to filter will require user input to work, since it will filter the entire output accordingly. E.g. if you filter for interactions with the gene product of TP53, the output will only show you genes, who’s corresponding proteins interact with p53.

Which data is displayed by default in the results?

Most of the available data will be shown by default, the only sections that currently have to be set to show to be displayed are the following: interactions, expression, cellular localisation and the keyword search. For a comprehensive list of default settings, refer to the section overview in the Output documentation.

How can I use the API?

Our API is simple and free to use without registration. Simply use the result hyperlink (https://genecascade.org/gd-cgi/results.cgi?) with json=1 and any other parameters relevant to your query. For examples and query parameters, please refer to the API documentation.

Why are some sections not listed in the Display Options (e.g. HPO and Orphanet)?

Since some sections can be used as filters in addition to being shown, they can be managed with the hide, show, filter radio button described in the FAQ above.

What does OMIM gene info mean?

While the OMIM section shows reports on various phenotypes related to the queried gene, the OMIM gene info section shows the gene specific OMIM report on the actual gene.

I set a spsection to show, why does the output not display any data for it?

Most likely there is no data available in our database for this specific category for the genes in your query. The show does not filter out genes for which we have no data for your section of interest. To show only those genes, you may want use the filter setting. Please note, that this works slightly different for the expression category (see next FAQ).

I filtered for expression, but the output shows me genes which don't seem to have any expression data for my selection, why?

The expression filter works a bit different than the rest of the GenDaB filters. GenDaB filters out only those genes which, according to our data, are explicitly not expressed in a certain tissues. Genes for which there is no data indicating that they are expressed or not expressed in the selected tissues, will still be included in the output.



If you have any additional questions, please refer to the GenDaB documentation or contact dominik.seelow AT bih-charite.de.

GenDaB - Legal

Contact

In case you discover bugs, have suggestions or questions, please write an e-mail to Dominik Seelow (dominik.seelow (at) bih-charite.de).
We also appreciate hearing about your general experiences using the database.

Imprint

Responsible for the purposes of media law for this page:
Dominik Seelow
Bioinformatics and Translational Genetics
Berliner Institut für Gesundheitsforschung
Charitéplatz 1
10117 Berlin
email: dominik.seelow (at) bih-charite.de

License

GenDaB is free and open to all users and there is no login requirement.