Microrna 3’-end modification detection algorithm and its usage example for tissue classification

Recent studies indicates that cellular cancerogenesis is connected with microRNA (miRNA) expression levels. In particular, different miRNAs can serve as lassification features for distinguishing different cancer types. This paper provides classification attempt using miRNA isoforms with 3’-end modification as classification features. microRNA samples was obtained using next generation sequencing method. Data was preprocessed using authors algorithm developed in R. Support Vector Mashines and Partial Least Square methods were used to classify two types of miRNA samples: Follicular Adenoma and Follicular Thyroid Cancer. It was observed that only several miRNA modified isoforms were identified as the most differentiating for analyzed samples. Obtained results indicate that miRNA 3’-end modifications can be used as cancer tissue classification features.