PacRAT: A program to improve barcode-variant mapping from PacBio long reads using multiple sequence alignment

Motivation: Use of PacBio sequencing for characterizing barcoded libraries of genetic variants is on the rise. PacBio sequencing is useful in linking variant alleles in a library with their associated barcode tag. However, current approaches in resolving PacBio sequencing artifacts can result in a high number of incorrectly identified or unusable reads. Results: We developed a PacBio Read Alignment Tool (PacRAT) that improves the accuracy of barcode-variant mapping through several steps of read alignment and consensus calling. To quantify the performance of our approach, we simulated PacBio reads from eight variant libraries of various lengths and showed that PacRAT improves the accuracy in pairing barcodes and variants across these libraries. Analysis of real (non-simulated) libraries also showed an increase in the number of reads that can be used for downstream analyses when using PacRAT. Availability and Implementation: PacRAT is written in Python and is freely available on Github (https://github.com/dunhamlab/PacRAT).