Modeling performance of sample collection sites using whole exome sequencing metrics

METHOD SUMMARY We utilized the whole exome sequencing quality control (QC) metrics from samples of Bristol Myers Squibb Immuno-Oncology clinical trials as a performance indicator. The QC step of the sample - genetic matching between the tumor and the blood samples from the same patient - defined two sources of potential sample failure: sample swap and cross-contamination. We performed Bayesian logistic regression to assess the relationship between QC success rate and relative site performance, adjusting for indication. Although next-generation sequencing assays are routinely carried out using samples from cancer trials, the sequencing data are not always of the required quality. There is a need to evaluate the performance of tissue collection sites and provide feedback about the quality of next-generation sequencing data. This study used a modeling approach based on whole exome sequencing quality control (QC) metrics to evaluate the relative performance of sites participating in the Bristol Myers Squibb Immuno-Oncology clinical trials sample collection. We identified several events for the sample swap. Overall, most sites performed well and few showed poor performance. These findings can increase awareness of sample failure and improve the quality of samples.