Backtrack

Backtrack is a robust computational method to discern low-abundance mutations from background error in ultra-deep sequencing data. We have shown that a beta-binomial distribution or aggregate negative binomial (NB) distributions describe PCR error depths in high-depth, targeted sequencing. Backtrack utilizes a statistical multi-sample approach that goes beyond estimating fixed detection thresholds allowed the discovery of variants with high confidence after false discovery correction.

Backtrack is implemented for MATLAB.