Biology – Quantitative Biology – Quantitative Methods
Scientific paper
2011-03-17
Biology
Quantitative Biology
Quantitative Methods
8 figures
Scientific paper
In searching differentially expressed mRNAs/genes in a microarray experiment, the two commonly used measures are the fold change and the t-test statistic (or the t-test p-value). The fold-change is a measure of differential expression "signal", whereas t-statistic is a signal standardized by the noise level, i.e., "signal-to-noise" ratio. The fold-change is an example of absolute effect size, whereas t-test a relative effect size. Both measures have shortcomings: fold change ignores the noise and does not provide an estimation of chance probability; on the other hand, the noise level, thus t-statistic, may not be estimated reliably when the sample size is small. To maximum utilization of statistical information from the data, fold-change and t-statistic can be displayed simultaneously by volcano plots. Volcano plots allow easy comparison between the "double filtering" gene selection criterion and "single filtering" or "joint filtering" criteria. Colored volcano plots provide a flexible way to incorporate external information such as pathway information of a gene. Stratified volcano plots permit examination of hidden patterns such as systematic change of differential expression with the average expression level. Overall, volcano plot is a useful visual tool in microarray analysis.
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