This will be the site for an announcement with a link to two signup pages?

The Galaxy/Rgenetics mashup presents two educational sessions as ancilliary events at ASHG in San Diego in 2007 - an hour for biologists, and a 2 hour workshop for software developers and bioinformaticians on the Tuesday of the opening.

Abstracts follow. Sign up to follow.

Session title: Integrated and freely available tools for vast genomic and disease association data: Brief (1hr) introduction to Rgenetics and Galaxy for biologists.

Presenters: Ross Lazarus, James Taylor and Anton Nekrutenko

Abstract: Fifteen years of continued public investment and exponential growth in freely available genomic data has not yet been matched with easy-to-use, scalable, integrated and flexible analytic tool capacity. Many experimental researchers are unable to use modern methods and vast data effectively, and the flood of genotype data soon to be released from large publicly funded human disease association studies through dbGaP will extend the gap between data and suitable tools even further.

The NIH Roadmap recognizes that many challenges in biomedical research will only be overcome by improved, integrative access to existing data and tools, so researchers can more effectively and rapidly translate their findings into clinical practice. For experimental biologists, intuitive and consistent interfaces, the ability to perform reproducible, multiple step analyses with outputs from one step feeding seamlessly to the next, minimal user training and effort, and a capacity to function efficiently at very large scale are needed. While many excellent stand-alone software packages are available, their integration into a convenient and coherent “one-stop-shop” for genetics and genomics remains a substantial technical challenge.

During this one-hour demonstration and tutorial, designed for biologists and researchers working with human and model-organism genetic and genomic data, participants will learn how to access and use genomic data through the Galaxy genomics workbench, an integrated and freely available resource. Statistical genetics tools that readily scale to whole genome data, currently being integrated into Galaxy by the Rgenetics project will be demonstrated, including convenient and easy to use integrated annotation and visualization of statistical results building on Galaxy’s seamless integration with the well known UCSC Genome Browser. Note that a more in-depth and hands-on educational workshop specifically intended for software developers and bioinformaticians will be offered in a separate session.

Supported by: NIH Grants 5R01HG003646-02, U01 HL065899-05, 5U54LM008748-02 and NSF Grant DBI-0543285

Session title: An extensible and scalable open-source framework for integrative genomics and statistical genetics: A hands-on workshop introducing Galaxy and Rgenetics, for bioinformaticians and software developers

Presenters: James Taylor, Anton Nekrutenko, and Ross Lazarus

Abstract: Access to easy-to-use, freely available, scalable, integrated and flexible analytic tools is currently lagging far behind access to the vast genomic data generated in 15 years of intensive public investment. Potentially important discoveries from the rich flow of public data are impeded by lack of accessible computational tools that transparently connect the growing diversity of large-scale data sources. Familiar desktop software packages and even basic programming skills are no longer sufficient for the analysis of tens of gigabytes of genomic alignments or billions of genotypes in whole genome human disease association studies. Genomic data discovery is no longer a limiting factor for much genomic research, and with the impending release of data from numerous publicly funded whole genome human disease association studies through dbGaP and related mechanisms, the situation for disease association and pharmacogenetics researchers will soon be a similar embarrassment of riches.

Galaxy is a mature, scalable and flexible open-source framework designed to be portable and readily extended with new functions and data sources. For data providers, Galaxy features a remarkably simple data access protocol requiring relatively little effort to implement. For computational researchers, lightweight open-source components, familiar deployment, and minimal effort for integration of local tools are featured. For experimental biologists, intuitive and consistent interfaces, the ability to perform reproducible, multiple step analyses with outputs from one step feeding seamlessly to the next, minimal user training and effort, and a capacity to function efficiently at very large scale are provided. Where privacy (e.g. for human subjects protection), or high throughput is needed, an initial functioning local Galaxy can be downloaded and installed in a few minutes.

This hands-on workshop is designed for bioinformaticians and software developers. Note that an introductory lecture-demonstration specifically for researchers/users will be offered separately during the conference. Workshop participants are asked to bring a wireless network capable laptop, and will work in small teams under expert tutor guidance, through a series of exercises designed to introduce the Galaxy genomics workbench. The Galaxy development team will support participants and guide progress and in addition to large scale genomics, the exercises will feature examples of new Galaxy statistical genetics tools that readily scale to whole genome data. By the end of the workshop, participants will have learned how to perform large scale genomics experiments, data transformation and visualization using Galaxy tools and data connectors, how to connect new data sources to Galaxy, and how to integrate existing non-interactive command line style executables into a Galaxy toolset.

Supported by: NIH Grants 5R01HG003646-02, U01 HL065899-05, 5U54LM008748-02 and NSF Grant DBI-0543285.