The rapid advancement of next-generation sequencing technology offers new perspectives in biomedical research and reshapes diverse fields. The tremendous amount of complex data generated by this novel technology has created a major challenge for statistical data analysis and interpretation. Although bioinformaticians have been heavily involved from the right beginning of the technology for sequence calling, alignment, assembly, and storage, the involvement of the statisticians to model the uncertainties and make statistical inferences has not been as extensive. From the development of the microarray technology, we know that the statistical analysis plays a central role in the effective application of high throughput technologies. We propose to organize a two-day conference to convene leaders in the field to discuss current statistical challenges and potential strategies for addressing these challenges. The goal of this conference are 1) to identify the challenges and opportunities in the relevant areas of statistical analyses, 2) to promote the involvement of statisticians in the data analysis for this technology, 3) to foster discussions and collaborations among methodologies, data analysts, and investigators, and 4) to disseminate the knowledge and lessons learned from this conference to the general scientific community. To fulfill the goals of the conference, the meeting is focused on two general topics: 1) data analyses for next-generation sequencing based DNA and RNA quantification, and 2) data analyses for sequencing-based genome diversity and complex disease studies. These topics cover the major applications of the technology that pose the most statistical challenges. Speaker presentations, poster presentations, and work groups will all contribute to fulfilling the objectives of the meeting.

Public Health Relevance

The rapid advancement of the next-generation sequencing technology offers new perspectives in biomedical research. However, the extraordinary amount of complex data creates a major challenge for statisticians and bioinformaticians. We propose a two-day conference for discussing the statistical aspects of the next-generation sequencing technology.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Conference (R13)
Project #
1R13HG005792-01A1
Application #
8062976
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Rossoshek, Anna
Project Start
2011-01-21
Project End
2012-12-31
Budget Start
2011-01-21
Budget End
2012-12-31
Support Year
1
Fiscal Year
2011
Total Cost
$20,000
Indirect Cost
Name
University of Alabama Birmingham
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Wu, Hao; Wu, Michael C; Zhi, Degui et al. (2012) Statistics for next generation sequencing - meeting report. Front Genet 3:128