Salon 1
The Next Generation of Genomic Data: Big Data and Single Cells (303705)
*RW Doerge, Carnegie Mellon UniversityFaye Zheng, Purdue University
Within the last decade sequencing technologies have scaled rapidly with respect to both throughput and accuracy. Independent of the material being sequenced (DNA or RNA), the capability of these new (next-generation) technologies to profile the molecular content of individual cells is now reality. Since the behavior of cells is dynamic, and conditioned on the setting in which the cell(s) exist (e.g., cancer, differentiation, etc.), the scientific community has great interest in interrogating cell-to-cell heterogeneity and understanding its biological consequences. At this point, the analysis of single-cell data is largely exploratory and significantly lacking from valid statistical investigations. As such, there is an opportunity for the analysis of single cell genomic data to benefit from proper experimental design, predictive modeling and hypothesis-based testing. The statistical and technological issues of single cell sequencing data will be discussed. Both simulated and real data will be employed to illustrate the unique features of single cell data as compared to current bulk-cell or bulk-tissue data. The hope for this talk is that it will stimulate awareness and thought from the statistical community on how to address data management, analysis and interpretation of these large complex data.