Data analysis for quantitative determinations of polar lipid molecular species

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dc.contributor.author Song, Tingting
dc.date.accessioned 2010-12-13T13:50:33Z
dc.date.available 2010-12-13T13:50:33Z
dc.date.issued 2010-12-13
dc.identifier.uri http://hdl.handle.net/2097/6907
dc.description.abstract This 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.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Lipidomics experiment en_US
dc.subject Mixed effect linear models en_US
dc.subject Categorical analysis en_US
dc.title Data analysis for quantitative determinations of polar lipid molecular species en_US
dc.type Report en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Statistics en_US
dc.description.advisor Gary L. Gadbury en_US
dc.subject.umi Statistics (0463) en_US
dc.date.published 2010 en_US
dc.date.graduationmonth December en_US


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