Bioinformatics
The Intraclass Transcriptome Correlation: Our lab developed the intraclass transcriptome correlation (ITC) as a summary statistic to compare degree of differential expression across an entire microarray (the transcriptome) and for quality control to determine signal strength and if all replicates within a treatment are consistent. The ITC can also be used for clustering.
The Generalized Family Wise Error Rate: A formidable challenge in the analysis of microarray data is the identification of those genes that exhibit differential expression. The objectives of this research were to examine the utility of simple ANOVA, one sided t tests, natural log transformation, and a generalized experiment wise error rate methodology for analysis of such experiments. As a test case, we analyzed a Affymetrics GeneChip microarray experiment designed to test for the effect of a CHD3 chromatin remodeling factor, PICKLE, and an inhibitor of the plant hormone gibberellin (GA), on the expression of 8256 Arabidopsis thaliana genes. The GFWER(k) is defined as the probability of rejecting k or more true null hypothesis at a given p level. Computing probabilities by GFWER(k) was shown to be simple to apply and, depending on the value of k, can greatly increase power. A k value as small as 2 or 3 was concluded to be adequate for large or small experiments respectively. A one sided t-test along with GFWER(2)=.05 identified 43 genes as exhibiting PICKLE-dependent expression. Expression of all 43 genes was re-examined by qRT-PCR, of which 36 (83.7%) were confirmed to exhibit PICKLE-dependent expression.
Profiling of abundant proteins associated with dichlorodiphenyltrichloroethane resistance in Drosophila melanogaster
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manuscript [PDF]
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Expression of Cyp6g1 and Cyp12d1 in DDT resistant and susceptible strains of Drosophila melanogaster
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manuscript [PDF]
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