T1DBase Frequently Asked Questions

Enter the identifier in the Search box found in the upper right corner. The Search accepts genes, genetic markers (SNPs), or candidate regions. Some example search terms are: INS, iNOS, interleukin, Il1-alpha, Hs.160562, 7098, IDDM1, Idd2, rs1000112. The results page has a summary of each gene, marker, or candidate region that matched the search term and provides links to pages with more information.

Gene pages pull together as much data about one gene as possible.  In light of the fact that disease-research can be focused on a gene, independent of the model organism in which it is studied, and that data from human is sometimes sparse, we have combined data from human, mouse and rat. In order to do so, we have combined data from a number of homology sources, including Homologene, RGD, and MGI.  As new information or tools become available, we add them to the gene page.

Creating an account is simple and fast; just fill out the short form on the login page (this page is accessible via the 'Log In' link in the upper right corner of most T1DBase pages). If you require access to private data, please include an email address when registering, and check the 'Request access to private data' box; we will then contact you by email to arrange the details.

Assuming that you are a member of the T1DGC, to get access to the T1DGC data, please create a user account on T1DBase (using the login page). Provide your email address when registering, and check the 'Request access to private data' box. We will then contact you via email with further details.
If you already have a T1DBase account please email us your username and we will arrange access.

The list of data sources is available by clicking on the number next to Version at the bottom of most T1DBase pages.

Currently, T1DBase has expression data and supplementary material for papers which can be downloaded. To see the public data available, click on the Downloads link in the navigation bar.

Confirmed Genetic Regions have been identified in one or more whole genome association studies, such as the recent WTCCC study and have been subsequently replicated in follow up experiments. A proposed resequencing region has been selected for further analysis and resequencing in a number of individuals in an attempt to identify further sequence variants for fine mapping of a genetic region.

T1DMart is a tool for retrieving marker and genotype data, and it outputs that data in a variety of formats. It is based on the ideas and libraries of the Biomart.

• You can retrieve marker information using lists of marker IDs, gene IDs, or chromosomal position; this marker information includes positions, aliases, associated assays, and functional data.
• T1DMart contains data for both NCBI35 and NCBI36, and can map between the builds.
• Genotype data can be filtered and output in PED format. For examples, please refer to the T1DMart Help page.

• Markers: dbSNP129, dbSNP130, DIL.
• Genotypes (public): HapMap CEPH, Han Chinese, Japanese, Yoruba; Swedish Cases/Controls from IPTR3 study.
• Genotypes (private): T1DGC data is available to relevant individuals; please contact us for details.

The data from a new T1DGC GWA study was combined with data from two other studies, to give a set of results with greater statistical power. Full information on this analysis is available in publication: Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Barrett JC, Clayton DG, Concannon P, Akolkar B, Cooper JD, Erlich HA, Julier C, Morahan G, Nerup J, Nierras C, Plagnol V, Pociot F, Schuilenburg H, Smyth DJ, Stevens H, Todd JA, Walker NM, Rich SS, The Type 1 Diabetes Genetics Consortium Nat Genet. 2009 PubMed ID: 19430480

T1DBase does not store individual level genotyping information from GWA studies. Due to access concerns this is best handled by a third party. We do however provide a comprehensive resource on how to gain access for interested parties. Please see the following page for further details.

All summary GWA results are available in Gbrowse. just make sure that you are using the Hs_NCBI36 data source and that the track T1DGC Meta-analysis p-values -log(p) is switched on. You can click on any point on the graph to drill down and be taken to a more detailed marker overview page.

The probable cause is that for the meta analysis not all studies were examined on the same platform. In these cases a method of imputation was implemented to allow comparison and calls for cases and controls etc. are therefore not available.

'WTCCC' stands for the Wellcome Trust Case Control Consortium. In a 2007 study, the WTCCC conducted genome-wide association studies to further the understanding of the genetics of 7 diseases, one of which was type 1 diabetes. The most significant results for type 1 diabetes are shown on the 'WTCCC Summary Data' page.

Currently, no. Due to the privacy concerns raised by a recent paper T1DBase does not show data from other diseases. For the full set of data you need to contact the Data Access team at the WTCCC.

Good question. A paper was recently published, demonstrating that if enough data is available, it is possible to identify an individual contributor within a genome-wide association study. Confidentiality is of the utmost importance, so we have removed the minor allele frequencies (MAFs) from T1DBase. After a thorough assessment of the implications of the technique, in collaboration with the WTCCC, they may be reinstated in the future. In the meantime, you can apply to the Data Access team at the WTCCC. for access to the MAFs.

Professor Linda Wicker at the DIL, University of Cambridge, in collaboration with Taconic, has constructed NOD Congenic Mouse Models that reproducibly alter the parental NOD phenotype and display varying levels of resistance from autoimmune diabetes. This tools shows which regions of the NOD genome have been altered in each of the strains developed.

For more information please visit the Taconic website.

The Generic Genome Browser (GBrowse) is a combination of database and interactive web pages for manipulating and displaying annotations on genomes.
Stein LD, Mungall C, Shu S, Caudy M, Mangone M, Day A, Nickerson E, Stajich JE, Harris TW, Arva A, Lewis S. The generic genome browser: a building block for a model organism system database. Genome Res. 2002 Oct;12(10):1599-610.

A GBrowse tutorial can be found here

There are a number of ways to view a gene/region in GBrowse. From a non-GBrowse page, enter the search term in the search box in the upper right corner of the page, and on the results page follow the GBrowse link to the relevant organism. From a GBrowse page select the data source of interest from the 'Data Source' and enter the gene or region to be displayed in the 'Landmark or Region' box.

BLAT is an effective tool for performing fast and accurate nucleotide alignments between genomic DNA and mRNA taken from the same species.
Kent WJ, BLAT--the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64.

Instead of searching a whole genome, BLAT search on T1DBase allows sequence based searches of Human T1D confirmed genetic regions and Mouse congenic regions maintained by T1DBase staff. It enables users to quickly identify whether and where a sequence overlaps with a known region of interest in T1D. The tool allows a genomic overview of hits which can be examined to provide further detail.

Currently we have 'Confirmed Genetic Regions' for human, these are constantly being updated in light of new genetic data.  We also have congenic regions for mouse -- these are accurately maintained through a close collaboration between T1DBase and Professor Linda Wicker and Dr Tom Brodniki.

We are currently curating our rat loci and hope to have them integrated by late 2009.

The BLAT tool is fully integrated into the T1DBase version of Gbrowse.  On the results page if you hover over a hit on the idiogram there is an option to visualize your hit in Gbrowse, by clicking on this you should easily be able to see your hit in genomic context.

The Beta Cell Gene Bank is a web accessible database that holds curated annotations for beta cell genes.

If you enter the name of a gene in the search box, the results for the search will include a link to the Beta Cell Gene Bank annotation if the gene is present in the Beta Cell Gene Bank.

The Beta Cell Gene Atlas (BCGA) contains basal gene expression data for genes in different beta cell sources - pancreatic beta cells, islets, whole pancreas, and beta cell lines -- from human, mouse, and rat. The term basal refers to expression profiles obtained from untreated (kept in culture or used right after collection). All data comes from microarray studies with the exception of a set of human islet data generated with MPSS (Massive Parallel Signature Sequencing is a sequencing based expression detection method which is described in this paper). Gene expression level estimates are based on signal intensities in the processed datasets for microarray studies and the actual counts are used for MPSS. The BCGA can be queried using any identifier that can be recognized by T1DBase. See the BCGA help page for more details on using the BCGA.

In case a gene is represented by more than one probe, we select the one that has the highest average intensity level across all the arrays in our microarray database. This solution was selected based on its wide spread usage in the microarray analysis community.

The normalization of gene expression data is rank transformation based on signal intensities within the array.  This normalization is performed before the data is added to T1DBase.

Tissue Expression contains human tissue and cell-type specific gene expression data from the Novartis GNF SymAtlas database.
Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR, Hogenesch JB (2004) A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004 Apr 20;101(16):6062-7

The normalization of gene expression data is rank transformation based on signal intensities within the array.  This normalization is performed before the data is added to T1DBase.

The Microarray Viewer shows differential gene expression across experimental conditions from 33 T1D-related studies. Microarray Viewer is a quick way of visualizing gene expression changes in relevant microarray sets. The results are expressed in terms of rank changes in experimental conditions versus matching control conditions. For example, an increase of 20 units for a particular gene means that the signal intensity of the gene went up 20 ranks in the experimental condition compared to control conditions.

The normalization of gene expression data is rank transformation based on signal intensities within the array.  This normalization is performed before the data is added to T1DBase.

If you think we left out a study that should be in the Microarray Viewer, please send us an email and we will analyze the data and upload it to our visualization tool.

The Meta Analysis Tool shows expression comparisons derived from studies found in the genomics section of the Beta Cell Biology Consortium. The results are displayed as a heat map with genes as rows and study comparisons as columns.

The Adobe Flash plugin is required to use this tool.

The Gene Dossier presents a concise table view of a gene or a list of genes emphasizing T1D-specific data.

The gene names, check mark icons, and magnifying glass icons are links that lead to more information.

• Human - A tick indicates that the gene is located either within a region of linkage disequilibrium of r²>0.4 with the most associated SNP of a genome wide association study and that this SNP has subsequently been replicated in a robust follow up study or the gene is found in a locus that has been identified and robustly replicated in multiple studies such as the INS loci. Clicking on the tick takes you to a locus poster page.
• Mouse - A tick indicates that the gene was found in a mouse linkage region. Clicking on the tick takes you to the mouse locus page.
• Rat - A tick indicates that the gene was found in a rat linkage region. Clicking on the tick takes you to the rat locus page.

We link publications to genes using information in several databases, including Entrez Gene, UniProt, and the Beta Cell Gene Bank. We filter these publications to generate a subset relevant to type 1 diabetes.

Connect the Dots is a translator for biological identifiers: it can translate among gene symbols, Entrez Gene IDs, Affymetrix probesets, and many more.  All the possible translations are shown on the Create Query screen.

The three main steps are:  you enter the identifiers you would like to translate, select the type of identifier from the drop-down menu, and select the identifier outputs you want. See the Connect the Dots help page for more details on using Connect the Dots.

Posters can be used to group specific topics or datasets, host supplementary material for publications, serve as a data distribution point for particular experiments, or share data among a group of collaborators.

To create a poster page you need to log in. If you have not already done so, you will need to create a new user account. Once logged in click the Poster Pages link in the left navigation bar and follow the 'create a new poster' link. You will then have the option to update the poster title from 'Untitled' to a name of your choice and to add a section by adding a section title and clicking the 'add section' button.

Posters can be shared with other registered T1DBase users by granting read permission on posters and poster sections. You will need to know the T1DBase username of the person with which to share the poster. Click on a poster and follow the 'Edit this poster' link at the top of a poster page.  Click on the 'Change poster privileges' link under the poster title. Grant read privileges on the poster by adding the username to 'Readers' section of the form and clicking the 'Add new reader' button. This allows the user to view the poster but not edit it. To allow a user to edit the poster, add them to the 'Writers' section of the form and click the 'Add new writer' button. To allow groups of people to read or edit the poster, change the drop-down menu to be 'group' instead of 'user' and add the groupname to the appropriate section of the form.

My T1DBase contains lists of genes, genetic markers (SNPs), and candidate regions (or loci). You can use these lists as starting points for many T1DBase programs. Some lists are pre-defined by T1DBase staff and are visible to all users. Other lists are created by users and are only visible to the user who created them.

T1DBase has many features which can only be used when the user has created an account and is logged in. Logging into T1DBase allows the user to create and save private lists, such as genes in a genomic region of interest, for use in subsequent logins. Lists of genes and markers can be used as input for several of the tools on T1DBase using the 'send list to tool' facility. Private data can also only be viewed and downloaded when logged in.

Cytoscape is an open source program for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other data. The Cytoscape project is an ongoing collaboration among several institutions and companies. Further information about Cytoscape is available at www.cytoscape.org.

T1DBase downloads data from several public sources. The interactions in these sources are combined, stored in the T1DBase database, and displayed using Cytoscape for T1DBase users.

KEGG pathways are maps representing molecular interaction and reaction networks.  The pathways are generated by the KEGG: Kyoto Encyclopedia of Genes and Genomes database.