Sample size considerations
cancer, cancer / non-cancer
CANCER
Enrolment for the LSRII data set continued until sufficient cancer samples were collected to build a robust model for automated analysis. For test development and model training, we needed enough cancer samples in order to create subsets of samples through repeated randomization that would allow us to evaluate cancer predictor selection without repeatedly ending up with the same small number of cancer samples driving the model fitting. With 28 out of 150 samples being a cancer sample (~ 19%), we would be able to create  > 3 million different training sets, each consisting of 100 samples (including 20 cancer samples, 20%). Three million different training sets are more than enough to test a wide range of potential parameters without a strong selection bias, while maintaining the cancer / non-cancer sample ratio of the entire sample set.The Navios data set represents the number of samples recruited between establishing the analysis pipeline and the start of drafting this manuscript.