m6anet leverages a Multiple Instance Learning framework to detect m6a modifications from Nanopore Direct RNA Sequencing data. To detect m6A modifications from your direct RNA sequencing sample, provide a tabular output of nanopolish-eventalign tool here. Behind the scenes, this m6anet tool first pre-processes the segmented raw signal file using ‘m6anet dataprep’ and then executes 'm6anet inference' function on its output to assign a probability that a modified read or site exists, which are returned as two separate tabulars from the tool to the history. |
hg clone https://toolshed.g2.bx.psu.edu/repos/iuc/m6anet
Name | Description | Version | Minimum Galaxy Version |
---|---|---|---|
to detect m6A RNA modifications from nanopore data | 2.1.0+galaxy0 | 23.0 |