Genome-wide associations studies (GWAS) have been very successful in identifying common genetic variation associated to numerous complex diseases. However, most of the identified common genetic variants appear to confer modest risk and few causal alleles have been identified. Furthermore, these associations account for a small portion of the total heritability of inherited disease variation. This has led to the reexamination of the contribution of environment, gene-gene and gene-environment interactions, and rare genetic variants in complex diseases. There is strong evidence that rare variants play an important role in complex disease etiology and may have larger genetic effects than common variants. Currently, much of what we know regarding the contribution of rare genetic variants to disease risk is based on a limited number of phenotypes and candidate genes. However, rapid advancement of second generation sequencing technologies will invariably lead to widespread association studies comparing whole exome and eventually whole genome sequencing of cases and controls. A tremendous challenge for enabling these “next generation” medical genomic studies is developing statistical approaches for correlating rare genetic variants with disease outcome.

The analysis of rare variants is challenging since methods used for common variants are woefully underpowered (e.g., accurately estimating allele frequencies in cases vs. controls requires ~10 observations of the minor allele; however, many of the functional rare alleles may be present only once in the resequence data). Therefore, methods that can deal with genetic heterogeneity at the trait-associated locus and that can be applied to both in cases vs. controls and quantitative trait studies are needed. Currently, these approaches are in their infancy and very basic criteria (such as functional annotation, sequence conservation, or biological pathway classification) are used. There is tremendous opportunity to apply data mining methods outside of the standard statistical toolkit to this problem. Additionally, deep sequencing will reveal many variants that are not causal, and in order to reduce the problems of misclassification, i.e. inclusion of non-causal variants and exclusion of causal variants in the analysis, it is beneficial to predict their potential functionality. Thus, methods to classify and annotate rare variants for subsequent analysis are necessary.

The session of PSB 2011 would focus on distilling current knowledge in assessing rare variant functionality and their correlation with complex traits, and more importantly bring forth methodological questions that need to be addressed for successful analysis of rare variants. “GWAS by sequencing” presents many new challenges and proposed solutions for interpreting sequencing data from clinical case/control cohorts will be of particular interest to a diverse audience. The session will similarly consider application-specific algorithms, analysis methods, or study planning and design tools with emphasis in the leveraging rare genetic variation in complex trait/disease correlation.

We encourage academic, government, and industrial scientists to submit manuscripts with original work in the subject area. PSB will publish accepted full papers in an archival proceedings indexed in Medline. All contributed papers will be rigorously peer-reviewed by at least three referees. A limited number of papers will be selected for oral presentation to the full assembled conference. Posters and computer demonstrations are also requested to complement the session, and require the submission of a one-page abstract. Accepted poster abstracts will be distributed at the conference separately from the archival Proceedings. In addition of the oral presentation of the full papers, and the poster session, an invited panel discussion devised to encourage exchange between industry and academic scientists will be also held.

The poster session at PSB is another possibility to present results or to share ideas in the Conference. Posters are exhibited several days during the conference and include topics from all PSB sessions.

Computer stations for live software or Web site demonstrations are also available during the conference and are encouraged as a complement to a poster or presentation.

In order to be included in the Abstracts booklet to be distributed at the conference, one-page posters abstracts should be submitted by November 1 to the online abstract submission form. Posters are not peer-reviewed nor indexed in MEDLINE.

The Pacific Symposium on Biocomputing (PSB 2011) is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. The symposium is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to the data-rich areas of molecular biology. PSB 2011 will be held January 3-7, 2011, on the Big Island of Hawaii.

For more information see the official PSB 2011 Web page: http://psb.stanford.edu