CMEIAS Sampling Statistics

In order to precisely estimate the diversity in any microbial community, many samples of that community need to be analyzed. The accuracy of the diversity level increases linearly with the sample size until the full level of diversity in the community is recognized. The larger the number, the better is the estimate. However, due to both time and economic constraints, collecting and analyzing the entire community is not feasible. Based on this real-world limitation in microbial community analysis, our goal in this project was to develop a mathematical software tool that can estimate the full level of morphological diversity in a microbial community based on a partial set of existing image analysis data. Our design of the project output is an interactive macro operating in Excel 2000 which creates several graphs displaying the relationship of diversity versus sample size of existing data, plus a result window displaying the desired results of sampling statistic computations. This tool will be very useful for microbial ecologists using the MSU-based CMEIAS program to analyze microbial community structure. Work done for the Department of Microbiology at Michigan State University, under the direction of Professor Frank Dazzo, in partial fulfillment of the requirements of Michigan State University MTH 844, advised by Professor Ronen Peretz.