Data analysis for quantitative determinations of polar lipid molecular species

dc.contributor.authorSong, Tingting
dc.description.abstractThis report presents an analysis of data resulting from a lipidomics experiment. The experiment sought to determine the changes in the lipidome of big bluestem prairie grass when exposed to stressors. The two stressors were drought (versus a watered condition) and a rust infection (versus no infection), and were whole plot treatments arranged in a 2 by 2 factorial. A split plot treatment factor was the position on a sampled leaf (top half versus bottom half). In addition, samples were analyzed at different times, representing a blocking factor. A total of 110 samples were used and, for each sample, concentrations of 137 lipids were obtained. Many lipids were not detected for certain samples and, in some cases, a lipid was not detected in most samples. Thus, each lipid was analyzed separately using a modeling strategy that involved a combination of mixed effects linear models and a categorical analysis technique, with the latter used for certain lipids to determine if a pattern of observed zeros was associated with the treatment condition(s). In addition, p-values from tests of fixed effects in a mixed effect model were computed three different ways and compared. Results in general show that the drought condition has the greatest effect on the concentrations of certain lipids, followed by the effect of position on the leaf. Of least effect on lipid concentrations was the rust condition.en_US
dc.description.advisorGary L. Gadburyen_US
dc.description.degreeMaster of Scienceen_US
dc.description.departmentDepartment of Statisticsen_US
dc.publisherKansas State Universityen
dc.subjectLipidomics experimenten_US
dc.subjectMixed effect linear modelsen_US
dc.subjectCategorical analysisen_US
dc.subject.umiStatistics (0463)en_US
dc.titleData analysis for quantitative determinations of polar lipid molecular speciesen_US


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