Gene ORGANizer was designed to provide researchers with the ability to analyze the phenotypic effects of genes and to understand the shared impact of groups of genes. The tool consists of two platforms: Browse and ORGANize. Browse allows users to see all of the body parts affected by a single gene of interest. ORGANize is designed to test which body parts, if at all, are over- or under-represented in a gene list. In both platforms, the user can base the analysis on either the typical phenotypes associated with a gene (defined as those that appear in >50% of sick individuals), or on its typical+non-typical phenotypes (i.e. any frequency). Additionally, the user can choose between confident associations (i.e. inferred from data on humans), and confident+tentative ones (inferred also from additional data on mouse and rat).
The output in both Browse and ORGANize comes in two forms: a color-coded body map and a table. The table contains all information whereas the body map visualizes most of it (125 out of the 146 body parts). Non-localized body parts (e.g. blood) or very small parts (e.g. sweat gland) do not appear in the body map and are represented only in the table. In the Browse option, the table and body map simply present the body parts that are phenotypically affected by the gene of interest, colored by the type of association (confident or tentative; typical or non-typical). Hovering over a body part in the table allows the user to see the phenotypes and diseases that are behind the gene–body part association. In the ORGANize option, the body map represents an interactive heat map, where significantly enriched or depleted body parts are colored based on the level of their enrichment or depletion. Non-significant body parts remain in their original gray color.
The enrichment and depletion tests within a gene list are carried out against a list of background genes. By default, the background consists of all genes that are linked to body parts in our DB. This background assures that even if certain anatomical parts are over-represented in the ontology (because some phenotypes are easier to detect, or some diseases are more studied), it would not bias the results (2 (link)). Gene ORGANizer also allows users to enter their own background list. User-specified backgrounds are useful in cases where the initial pool of genes from which the gene list was derived contains an inherent bias. For example, in a list of genes that were found to be differentially regulated based on a microarray experiment, the background should comprise only genes that are represented on that microarray.
The output in both Browse and ORGANize comes in two forms: a color-coded body map and a table. The table contains all information whereas the body map visualizes most of it (125 out of the 146 body parts). Non-localized body parts (e.g. blood) or very small parts (e.g. sweat gland) do not appear in the body map and are represented only in the table. In the Browse option, the table and body map simply present the body parts that are phenotypically affected by the gene of interest, colored by the type of association (confident or tentative; typical or non-typical). Hovering over a body part in the table allows the user to see the phenotypes and diseases that are behind the gene–body part association. In the ORGANize option, the body map represents an interactive heat map, where significantly enriched or depleted body parts are colored based on the level of their enrichment or depletion. Non-significant body parts remain in their original gray color.
The enrichment and depletion tests within a gene list are carried out against a list of background genes. By default, the background consists of all genes that are linked to body parts in our DB. This background assures that even if certain anatomical parts are over-represented in the ontology (because some phenotypes are easier to detect, or some diseases are more studied), it would not bias the results (2 (link)). Gene ORGANizer also allows users to enter their own background list. User-specified backgrounds are useful in cases where the initial pool of genes from which the gene list was derived contains an inherent bias. For example, in a list of genes that were found to be differentially regulated based on a microarray experiment, the background should comprise only genes that are represented on that microarray.
