Best: A Tool for Characterizing Sequencing Errors

Platform-dependent sequencing errors must be understood to develop accurate sequencing technologies. We propose a new tool, best (Bam Error Stats Tool), for efficiently quantifying and summarizing error types in sequenced reads. best ingests reads aligned to a high-quality reference assembly and produces per-read metrics, summary statistics, and stratified metrics across genomic intervals. We show that best is 16 times faster than a prior method. In addition to being useful for improving the accuracy of sequencing platforms, best can also be applied to evaluate and improve other experimental factors such as library preparation and error correction methods. ### Competing Interest Statement DL conducted this work as a paid student researcher at Google. AB, KS, PCC, AC, and DEC employees of Google LLC and own Alphabet stock as part of the standard compensation package. This study was funded by Google LLC.