I have seem some platforms such as GEPIA offering ANOVA for differential gene expression analysis. However, as far as I’m concerned, ANOVA compares the averages and assumes equal distribution and variance among samples, which, as far I have been lead to assume, is uncommon for any kind of RNA-seq derived data, especially considering the thousands of possibly expressed genes in the human genome. Is ANOVA really appropriate for differential expression?
Nope. Also the distribution of RNA-seq data is not normal (as an ANOVA also assumes). You should use specifically designed tools such as edgeR, DESeq2 or limma.
According to A Beginner’s Guide to Analysis of RNA Sequencing Data (www.atsjournals.org/doi/10.1165/rcmb.2017-0430TR) ANOVA is an appropriate analysis for RNA-seq data. However, the review doesn’t specify a tool/package to do this analysis. Searching for how to do ANOVA on RNA-seq data brought me to this page.