Enrichment analysis is an effective tool to interpret gene expression data generated by high throughput genomic analysis. Enrichment analysis can be applied to differential exon expression data generated by RNA-seq. However, the enrichment analysis based on differential exon expression introduced unknown exon number bias. Gene ontology terms related to the genes that have larger number of exons tend to be more significant in the enrichment analysis. To correct this exon number bias, we adopted two approaches. First approach is to apply non-central hypergeometric distribution to test significance of each term. Second approach is to count exon number instead of gene number. We confirmed that exon number bias had been adjusted by non-central hypergeometric distribution approach.