Response to Letter to the Editor entitled ‘Correct microarray analysis approaches in “Hsa-circRNA11783-2 in peripheral blood is correlated with coronary artery disease and type 2 diabetes mellitus”’

Abstract

In the paper entailed ‘Hsa-circRNA11783-2 in peripheral blood is correlated with coronary artery disease and type 2 diabetes mellitus’, we illustrated the correlation of circRNA with T2DM and CAD. We used the common method - Q-PCR to select differentially expressed circular RNA (differentially expressedgenes(DEGs)), with a criteria of fold change>2 and unadjusted p values < 0.05 in expression. When the candidate RNAs have been narrowed down by GO and Pathway analysis, Q-PCR is a good verification method, although the idea that using Q-PCR to verify all the DEGs is still unrealistic. There is no denying that using an optimal statistical approach makes the survey much easier.

Dear Editor,

Thank you for your letter. The suggestions mentioned are very important and conducive to our future research. The following are our replies:

1. As discussed in our article, we illustrated the correlation between hsa-circRNA11783-2 and coronary artery disease and type 2 diabetes mellitus. In our research, we found that if we used (Benjamini and Hochberg (B-H)) corrected p-value during the stage of initial screening of differentially expressed circRNAs, the selected circRNAs, satisfying the criterion of p < 0.05, were deficient quantitatively for the further research. Therefore, to get as many candidate circRNAs as possible, we chose the unadjusted p-value <0.05 and fold change (FC) >2 as our screening criteria, which is not a wrong method; meanwhile, many researchers did choose the unadjusted p-value <0.05 as criterion for the same reason. ¹

2. The limma model mentioned in the letter is indeed frequently used in the microarray field, but our chips for microarray analysis are designed by CapitalBio and produced by Agilent Company, and the result of microarray was also analysed with the officially supported software GeneSpring. Agilent Company is a leading enterprise specializing in microarray analysis. At the same time, GeneSpring is widely used in researches of the non-coding RNA field.^2–4 So, the results of GeneSpring seem to be rather credible.

3. In the field of microarray analysis, it is crucial that the result of microarray should be tested by some statistical approach in order to narrow the scope of RNA down and to select the candidate RNAs, and it is of equal importance to verify the expression level of the candidate RNA by Quantitative Real-Time Polymerase Chain Reaction (Q-PCR). None of the two methods can be dispensed with.

Thanks again for the valuable suggestions.