External Source Data

GeneWeaver utilizes several external data sources to provide users with a rich set of genomic features and gene associations.

These data sources include:

• Ensembl
• Entrez
• UniGene
• MGI
• HGNC
• RGD
• ZFIN
• FlyBase
• Wormbase
• SGD
• miRBase
• CGNC

Background

Why bother with all these external data sources? Why not just use one?

In genomics research, there are different types of gene and microarray identifiers because the same gene can be referred to by different names or IDs, depending on the context or the source of the information. This can happen even for genomic features within the same species! All these different identifiers can create confusion and make it difficult to compare and integrate data from different sources.

Why are there so many different identifiers, you ask? There are a multitude of reasons, some of which are historical, some of which are technical, and some of which inherent to biology.

A given gene may have multiple names or IDs that have been used in different contexts as a result of how naming and annotation has evolved over time. It also can be the case that different databases just used different conventions. Annotations and naming conventions are also updated as new information about the function and structure of genes becomes available.

Genotype platforms, the methods or tool used to identify and detect genetic variations, can differ in their design and layout, which can affect the way genes are represented. This can lead to different probe IDs or other identifiers being used to refer to the same genomic features on different platforms.

Genomic feature identifiers can also differ between different species, since different organisms have different sets of genes and thus different naming conventions for those genes. Even if the same identifier is used across species, it may not refer to the same genomic feature, and the genomic feature itself might have entirely different function.

GeneWeaver's Solution

GeneWeaver solves this problem by integrating data from multiple sources (listed above) and mapping all the different identifiers to a single, unified set of internal identifiers.

This allows researchers to upload data from different sources to the same platform, and allows tools to operate of data from different sources without having to worry about the differences in the identifiers used by those sources.

Geneweaver also uses homology information to map paralogs and orthologs (collectively knows as homologs) across and within species. This allows researchers to perform cross-species analysis, and to identify conserved and divergent biological functions.

This concept is explained in more detail in the Geneweaver Data Model concepts page, and in the Data model reference page.