Bioinformatics Analysis of Differential Innate Immune Signaling in Macrophages by Wild-Type Vaccinia Mature Virus and a Mutant Virus with a Deletion of the A26 Protein

LETTER

We read with great interest the recent report by Siti Khadijah Kasani et al. in the Journal of Virology, “Differential innate immune signaling in macrophages by wild-type vaccinia mature virus and a mutant virus with a deletion of the A26 protein” (1), which was posted online on 28 June 2017. The results of the report are very helpful for us; however, from our perspective, the authors' methods of bioinformatics analysis are inappropriate.

We noticed that the authors only considered gene expression values for detecting differentially expressed genes (DEGs) of bone marrow-derived macrophages (BMDM) infected by WR and WRΔA26 compared to mock-infected BMDM. Actually, because of the high false positivity rate caused by using a huge number of probes and multiple comparisons, it is fundamental to analyze microarray data properly to reach a reliable result by a rational statistical method. Obviously, only selecting genes with a 2-fold change in expression is not reliable and suitable for high-level microarray analysis. From our perspective, we recommend using specialized high-level microarray analysis, limma (Linear Models for Microarray Analysis) (2), a commonly used package of statistical tests for analysis of differential expression by using linear models, and choosing more than 1.5-fold expression changes and a false-discovery rate of <0.05 as the cutoff is an appropriate and conservative approach to obtain differentially expressed genes (DEGs). Moreover, Significance Analysis of Microarrays (3) is also a considerable nonparametric statistical algorithm, and a 2-fold expression change and a q value of <0.1 is a rational cutoff to obtain DEGs.

Above all, although the authors performed extra analysis for a portion of DEGs in order to verify the results of the microarray, it is impractical to use quantitative reverse transcription-PCR or other technology to verify all DEGs. Choosing the right statistical method (4) and obtaining more accurate and convincing results of DEG analysis is the basis for further analysis such as ingenuity pathway analysis.