Generally in microarray differential expression analysis studies the lower bound for |logc| is chosen around 1 to make fold change 2 which sounds like a common sense. In other cases, when |logfc| >= 1 gives zero differentally expressed genes, logfc is chosen to get a "reasonable" amount of differentially expressed genes. It stands to reason, that a more rational way of choosing logfc would be to infer it from the microarray platform's accuracy or the quality of the hybridizations in the particular microarray-experiment or some other evidence-based criteria.
How to decide which logfc to choose?
Hello
As you know, usually we consider fold change 2 as a threshold. If you have your own reason (might be technical) to change this threshold, the best way is experimental validation of some your transcript, then correlate your laboratory data with the array results, then you may set a new threshold for your experiment.
The fold change or log-fold change can be used as a measure of effect size in
high throughput experiments including gene expression analysis. However, the statistical significance obtaine from repetitions is another important number. One can used multiple testing adjusted p-values or false discovery rate values and ofte it is then advisable by plotting everything as a volcano plot, where log-fold change of each gene is on the x-axis and the log10 p-value (adjusted) is on the y-axis. I recommend the limma package in R to do such an analysis.
- Badges
- Science topic
- Similar topics
- Biological Science
- Molecular Biology
- Molecular Methods
- Cloning