m6Adecom: Analysis of mA profile matrix based on graph regularized non-negative matrix factorization.

Epitranscriptomic mA methylation is shown to mediate extensive regulations under the context of various RNA binding protein (RBP) readers. With mA methylation data has reached a sizable scale, the functional context-aware analysis of mA profiles is becoming more feasible and demanded. In this study, we employed graph regularized non-negative matrix factorization (GNMF) for mA profile analysis and comparison, where the RBP binding preference of mA sites were incorporated as the functional context-based graph constraint term. Compared to the baseline non-negative matrix factorization (NMF) method, this GNMF-based method could better capture the distinctions in multiple functional characteristics between different group of mA sites, including but not limited to the associated biological pathways and disease genes. We further established m6Adecom, an online tool that can be used for correlation and enrichment analysis of mA profiles using the matrix decomposition result from GNMF, and gene set enrichment analysis based on the high-score mA sites. m6Adecom is freely accessible at http://www.rnanut.net/m6adecom.