mAexpress-Reader: Prediction of mA regulated expression genes by integrating mA sites and reader binding information in specific- context.

N-methyladenosine (mA) is the most abundant form of mRNA modification and plays an important role in regulating gene expression. However, the mechanisms of mA regulated gene expression in cell or condition specific, are still poorly understood. Even though, some methods are able to predict mA regulated expression (mA-reg-exp) genes in specific context, they don't introduce the mA reader binding information, while this information can help to predict mA-reg-exp genes and more clearly to explain the mechanisms of mA-mediated gene expression process. Thus, by integrating mA sites and reader binding information, we proposed a novel method (called mAexpress-Reader) to predict mA-reg-exp genes from limited MeRIP-seq data in specific context. mAexpress-Reader adopts the reader binding signal strength to weight the posterior distribution of the estimated regulatory coefficients for enhancing the prediction power. By using mAexpress-Reader, we found the complex characteristic of mA on gene expression regulation and the distinct regulated pattern of mA-reg-exp genes with different reader binding. mA readers, YTHDF2 or IGF2BP1/3 all play an important role in various cancers and the key cancer pathways. In addition, mAexpress-Reader reveals the distinct mA regulated mode of reader targeted genes in cancer. mAexpress-Reader could be a useful tool for studying the mA regulation on reader target genes in specific context and it can be freely accessible at: https://github.com/NWPU-903PR/m6AexpressReader.