MuTect takes as input sequence data from matched tumor and normal DNA after alignment of the reads to a reference genome and standard preprocessing steps38–40, which include marking of duplicate reads, recalibration of base quality scores and local realignment. The method operates on each genomic locus independently and consists of four key steps (Fig. 1): (i) Removal of low-quality sequence data (Supplementary Methods); (ii) variant detection in the tumor using a Bayesian classifier; (iii) filtering to remove false positives resulting from correlated sequencing artifacts that are not captured by the error model; and (iv) designation of the variants as somatic or germline by a second Bayesian classifier.
