*4.5. Differential Expression Analysis*

Differential expression analysis of two conditions or groups was performed using the DESeq R package (1.18.0, http://www.bioconductor.org/packages/release/bioc/html/DESeq.html) [54]. DESeq provides statistical routines for determining differential expression in digital gene expression, lncRNAs, circRNAs, and miRNAs expression data, using a model based on the negative binomial distribution. The resulting P values were adjusted using the Benjamini and Hochberg's approach for controlling the false discovery rate. Genes, lncRNAs, and circRNAs with an adjusted *p*-value < 0.01 and an absolute value of log2 (Fold change) > 1 found by DESeq were assigned as differentially expressed. miRNAs with an adjusted *p* < 0.05 found by DESeq were assigned as differentially expressed (Supplied by BioMarker, Beijing, China).
