Biological Sciences: Sharon Stranford (Mount Holyoke College)
Using a mouse model of AIDS (called MAIDS) to study genetic and cellular determinants of susceptibility to immune deficiency, we can create infection resulting in a chronic and life-threatening AIDS-like disease in one strain (C57BL/6) and a mild, resolvable illness in the other strain (BALB/c). We study differential responses within the lymphoid tissues (spleen and lymph node) between the two strains in the first 2 weeks post infection for clues to productive immune response pathways. These studies have involved using DNA microarrays to identify differential gene expression, followed by some limited real time PCR assays and protein-based assays on individual genes/proteins in an attempt to confirm these differences. We published our first joint math and biology collaboration on this work in Immunogenetics (Tepsuporn et al. 2008).
We would now like to evaluate the methods used for computational analysis and how these relate to biological outcome. For each of methods, we would convert the statistic to an estimated false discovery rate and use this value to identify differentially expressed genes. Using a systematically varying collection of artificial data, each method can then be compared for accuracy of FDR estimation and success at identifying differentially expressed genes. These alternative methods can also be used to reanalyze our actual data sets and compare the outcomes. We used the permutation methods in our statistical analysis of differential expression and would like to compare this with a principle component analysis, an empirical Bayes procedure, and a hierarchical Bayesian analysis. Students would be involved in all laboratory work and analysis.