Brieno turns raw nanopore current into discrete tokens, then pretrains a Transformer that reads methylation with few labels
Raw nanopore current is continuous and has no native token vocabulary, and prior analyses built a separate model per task. Brieno first compresses the signal into discrete tokens with residual vector quantization, then pretrains a Transformer by masked-token prediction on 118 million reads, so frozen or fine-tuned features serve species identification, barcode demultiplexing, basecalling and methylation detection. On held-out runs, fine-tuned Brieno reached a read-level CpG 5mC AUROC of 0.978, above the 0.975 of Dorado's dedicated 5mCG model.