ModiDeC: a multi-RNA modification classifier for direct nanopore sequencing.

ABSTRACT: RNA modifications play a crucial role in various cellular functions. Here, we present ModiDeC, a deep-learning-based classifier able to identify and distinguish multiple RNA modifications (N6-methyladenosine, inosine, pseudouridine, 2'-O-methylguanosine, and N1-methyladenosine) using direct RNA sequencing. Alongside ModiDeC, we provide an extensive database of in vitro-transcribed and synthetic sequences generated with both the new RNA004 chemistry and the old RNA002 kit. We show that RNA modifications can be accurately recognized and distinguished across different sequence motifs using synthetic data as well as in HEK293T cells and human blood samples. ModiDeC comes with a graphical user interface and an Epi2ME pipeline that allows easy customization and adaptation to specific research qu

SUBMITTER: Alagna N 

PROVIDER: S-EPMC12276011 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature