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Microarray data analysis for SNP effects and inferring alternative splicing

Posted on:2009-12-13Degree:Ph.DType:Dissertation
University:The University of Alabama at BirminghamCandidate:Chen, LangFull Text:PDF
GTID:1440390005450505Subject:Statistics
Abstract/Summary:
Microarrays are technologies that enable scientists to measure gene expression at the genomic-wide level in a single assay. Microarrays are able to quantitate gene expression by taking advantage of the double helical structure of deoxyribonucleic acid (DNA). Nucleic acids such as ribonucleic acid (RNA), from a sample, will bind to complementary sequence probes on a solid substrate. However, small changes in the sequence of the sample or the probe will result in diminished binding of the samples to the probes. In this study we conducted an in depth evaluation and quantification of the effect of single nucleotide polymorphisms (SNPs) on gene expression. We then developed methods for assessing changes in gene expression due to SNP from those due to alternative splicing. Finally, we map potential genetic loci that control the alternative splicing (asQTL).
Keywords/Search Tags:Gene expression, Alternative
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