LAUSR

MicroRNAs(miRNAs) are small and non-coding RNAs that can regulate gene expression by binding on the 3’UTR of target mRNAs and inhibiting mRNAs to translate protein, or even promoting mRNAs degradation. In various complex disease and pathological conditions, we can identify dysregulated which are the causative factors. Therefore, it is an essential approach to explore the interactions between miRNA and gene in certain diseases, such as cancers. However, challenge arises when we are trying to validate the interactions by doing bench experiments. The numbers of miRNA-gene interactions are too large to be validated. Currently, most prediction algorithms only provide its own result and low consistency rates across independent methods have been reported. Therefore, it is necessary to develop a systematic method to perform a comprehensive analysis by using the expression profiles from genes and miRNAs concurrently. To address these issues, we developed an R package named as anamiR. AnamiR is able to perform an integrated analysis of mRNA and miRNA with the phenotype information. The analysis procedures are briefly summarized as the follows. Initially, differential expression analysis would be applied to the raw data. Subsequently, the anamiR package can identify significant pairs of miRNAs and genes if their Pearson correlation coefficients are lower than the pre-defined threshold. Next, the significant pairs were compared to the embedded database in anamiR, which included two validated and several predicting miRNA-gene databases. Lastly, functional analysis is also available in this package to characterize the biological functions and signaling pathways of dysregulated miRNAs and genes. A breast cancer dataset was analyzed by using anamiR, which identified nine miRNA-gene interactions for deeper studying. Among these interactions, there are two miRNAs and nine genes included. miR-497-5p and miR-204-5p which both were mentioned in breast cancer frequently, are found by anamiR. The anamiR package is freely available at Bioconductor. Citation Format: Ti-Tai Wang. An integrated analysis package of miRNA and mRNA expression dataAn integrated analysis package of miRNA and mRNA expression data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4427. doi:10.1158/1538-7445.AM2017-4427