Gladstone scientists announce new version of bioinformatics software program

A team of scientists at the J. David Gladstone Institutes has unveiled a new version of GenMAPP, a widely used software program designed to help biomedical scientists view and analyze genome-scale data sets in the context of biological pathways.

GenMAPP 2.0, short for Gene Map Annotator and Pathway Profiler, marks the first major revision of the program, which was developed and launched by Gladstone scientists in 2002. With the program having been freely available at www.GenMAPP.org to all researchers since its debut, it has now become a standard means of depicting and sharing biological data and pathway information.

As GenMAPP developer Bruce Conklin, MD, points out, a single genomics experiment can yield enough data to fill a large telephone book, and methods for organizing and analyzing the data are desperately needed.

"Genomic experiments can easily overwhelm a scientist with data," explained Conklin, an investigator at the Gladstone Institute of Cardiovascular Disease and UCSF associate professor of medicine, molecular and cellular pharmacology. "GenMAPP organizes the data by biological process, a scheme that most biologists understand, and allows us to find new connections that we would not have seen otherwise."

From its beginnings, GenMAPP has been designed for viewing and analyzing gene expression data on biological pathways and other groupings of genes. GenMAPP 2.0 incorporates a variety of new features, many of them suggested by users, including:

A flexible format that accepts many different gene ID systems from resources for many species, including human, Drosophila (fruit fly), mouse, rat, zebrafish, C. elegans (a microscopic roundworm), and S. cerevisiae (yeast).
Species-specific gene databases that show relationships between the various gene ID systems in the database. For example, genes on the MAPP (GenMAPP files that represent biological pathways or groupings of genes) may use a single common ID type and the expression data sets may be annotated with a completely different ID type, but GenMAPP provides an internal database that can connect the two gene IDs.
Assistance in creating unique Gene Databases for any species, as well as customization of existing Gene Databases.
The ability to export (as HTML) entire sets of MAPPs, including information from the researcher's Expression Dataset, enabling convenient, interactive display of data on web sites.

By viewing genes in the context of a known biological process, GenMAPP makes it possible to make sense of data that might otherwise be difficult to interpret. The most widespread alternative analytical method, hierarchical clustering, groups genes without knowledge of the gene's function, but it can miss small changes in expression. In fact, the two methods complement each other in interpreting biological data.

GenMAPP was developed with grant support from the NIH. Any scientist can use it to modify MAPPs to fit other hypotheses, to design new pathways, or to share the data with others in the research community.

The GenMAPP site has logged over 10,000 registrations to download the program, and GenMAPP has been cited as a resource in upwards of 50 publications to date.

"We have been very pleased with the widespread acceptance and use of GenMAPP," said Conklin. "This new version was created in response to comments from those many users, and I am excited about what it will do for biomedical research here and around the world."

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The J. David Gladstone Institutes is an independent, nonprofit biomedical research institution affiliated with UCSF. For further information, visit www.gladstone.ucsf.edu.

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