Genetic recombinant analysis of TGCE data
Analysis of recombinant inbred lines is used to generate data needed for the creation of genetic maps of organisms. Using these genetic maps, the functions of genes can be discovered. To be most useful, the genetic map needs to be of high density. Genetic map density can be increased by using a process called Temperature Gradient Capillary Electrophoresis (TGCE) to detect small polymorphisms between genetic alleles. This thesis introduces a software tool called GRAMA (Genetic Recombinant Analysis and Mapping Assistant) which is able to analyze data from recombinant inbred lines subjected to TGCE and present automated results to the user in an intuitive visual format. Data from multiple TGCE runs are integrated to display all necessary data simultaneously. GRAMA contains its own algorithm to detect peaks from electropherogram data produced by TGCE. Results from GRAMA's algorithm are compared with results from another software package used to evaluate electropherograms and differences are flagged for further analysis. GRAMA produces two sets of consensus scores as output. One set of scores provides the user with very detailed information that encodes all possible experimental results, while the other summarizes these results into mapping scores that can be used as direct input for a genetic mapping program. Experiments reveal that GRAMA generates highly accurate results and boosts user productivity more than two-fold relative to previous methods used to perform recombinant inbred analysis of TGCE data.