FBCwPlaid: A Functional Biclustering Analysis of Epi-Transcriptome Profiling Data Via a Weighted Plaid Model

Recent studies have shown that in-depth studies on epi-transcriptomic patterns of N6-methyladenosine (m(6)A) may help understand its complex functions and co-regulatory mechanisms. Since most biclustering algorithms are developed in scenarios of gene expression analysis, which does not share the same characteristics with m(6)A methylation profile, we propose a weighted Plaid biclustering model (FBCwPlaid) based on the Lagrange multiplier method to discover the potential functional patterns. Each pattern is achieved by minimizing approximation error between FBCwPlaid predicted value and real data. To address the issue that site expression level determines methylation level confidence, it uses RNA expression levels of each site as weights to make lower expressed sites less confident. FBCwPlaid also allows overlapping biclusters, indicating some sites may participate in multiple biological functions. FBCwPlaid was then applied on MeRIP-Seq data of 69,446 methylation sites under 32 experimental conditions, each of which represented a stimulus to a particular cell line or environment. Finally, three patterns were discovered, and further pathway analysis and enzyme specificity test showed that sites involved in each pattern are highly relevant to m(6)A methyltransferases. Further detailed analyses showed that some patterns are condition-specific, indicating that some specific sites' methylation profiles may occur in specific cell lines or conditions.