2passtools: two-pass alignment using machine-learning-filtered splice junctions increases the accuracy of intron detection in long-read RNA sequencing

Abstract Vegetable / Fruit Slicers Transcription of eukaryotic genomes involves complex alternative processing of RNAs.Sequencing of full-length RNAs using long reads reveals the true complexity of processing.However, the relatively high error rates of long-read sequencing technologies can reduce the accuracy of intron identification.Here we apply alignment metrics and machine-learning-derived sequence information to Power Liftgate Kit filter spurious splice junctions from long-read alignments and use the remaining junctions to guide realignment in a two-pass approach.

This method, available in the software package 2passtools ( https://github.com/bartongroup/2passtools ), improves the accuracy of spliced alignment and transcriptome assembly for species both with and without existing high-quality annotations.

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