PacBio announced a research collaboration with Google. Under the terms of the collaboration, PacBio will explore the use of Google's genomic analysis, machine learning and algorithm development tools to further improve PacBio's already highly accurate variant calls for HiFi sequencing runs, unlocking more insights from PacBio sequencing data. The collaboration builds on previous research from PacBio and Google.

A recent publication on the work available on bioRxiv, Deep Consensus: Gap-Aware Sequence Transformers for Sequence Correction, yielded improvements in variant calling and suggested that Google's DeepConsensus machine learning tool is capable of increasing the yield of 99.9% accurate HiFi reads by as much as another 27% per instrument run. PacBio hopes to improve the utility and overall value of HiFi data specifically for applications such as whole genome sequencing (WGS), full-length isoform, and targeted sequencing applications by integrating Google's deep learning technology into its future product releases.