Biomedical subjects
Publications and source records attributed to Leslie M Cope.
A comment on Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset by SE Choe, M Boutros, AM Michelson, GM Church and MS Halfon. Genome Biology 2005, 6:R16.
CD4 + lymphocytes play a key role in asthma pathogenesis, but much remains unknown about the genetic mechanisms that affect disease severity. In this study we sought to investigate global patterns of gene expression in CD4 + lymphocytes isolated from subjects with severe asthma through the use of microarray technology. CD4 + lymphocytes were separated from peripheral blood, total RNA was purified, and biotinylated complementary RNA was prepared and hybridized to Affymetrix HU133 chips (Affymetrix, Santa Clara, Calif). Using the robust multi-chip average procedure, we compared the messenger RNA expression profiles of more than 33,000 genes of CD4 + lymphocytes in subjects with severe ( n = 5) and mild ( n = 5) asthma. Forty genes had 2-fold mean expression differences or greater. Thirty-seven genes were up-regulated, including transforming growth factor-beta and those involved in T-cell activation, proliferation, and cytoskeletal changes. Three genes were down-regulated, including the T-cell-receptor delta locus. This study demonstrates a method by which CD4 + lymphocytes can be extracted from blood for the purpose of microarray analysis. Furthermore, we show that T-lymphocytes from the peripheral blood of subjects with severe and mild asthma differ in their gene-expression profiles, supporting the view that asthma is a systemic disease. These differentially expressed genes identify potential molecular targets for preventive and therapeutic options for severe asthma.
MOTIVATION: The defining feature of oligonucleotide expression arrays is the use of several probes to assay each targeted transcript. This is a bonanza for the statistical geneticist, who can create probeset summaries with specific characteristics. There are now several methods available for summarizing probe level data from the popular Affymetrix GeneChips, but it is difficult to identify the best method for a given inquiry. RESULTS: We have developed a graphical tool to evaluate summaries of Affymetrix probe level data. Plots and summary statistics offer a picture of how an expression measure performs in several important areas. This picture facilitates the comparison of competing expression measures and the selection of methods suitable for a specific investigation. The key is a benchmark data set consisting of a dilution study and a spike-in study. Because the truth is known for these data, we can identify statistical features of the data for which the expected outcome is known in advance. Those features highlighted in our suite of graphs are justified by questions of biological interest and motivated by the presence of appropriate data.
High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike-in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated.