Versatile Quality Control Methods for Nanopore Sequencing

Abstract

Third-generation sequencing using nanopores as biosensors has recently emerged as a strategy capable to overcome next-generation sequencing drawbacks and pitfalls. Assessing the quality of the data produced by nanopore sequencing platforms is essential to decide how useful these may be in making biological discoveries. Here, we briefly contextualized NanoR, a quality control method for nanopore sequencing data we developed, in the scenario of preexistent similar tools. We also illustrated 2 quality control pipelines, readily applicable to nanopore sequencing data, respectively, based on NanoR and PyPore, a second quality control method published by our group.