Fig. 2

DeviCNV workflow. Analysis-ready BAM files were used for DeviCNV input. After read-depth normalization for chromosome X, DeviCNV filters low-quality samples from the input dataset. Then, DeviCNV builds N (1,000 by default) linear regressions per probe (or amplicon) to predict a read-depth ratio and confidence interval per probe for each sample. By combining signals of probe-level read-depth ratios, DeviCNV calls raw CNV candidates and evaluates them using a new scoring system. Finally, DeviCNV provides a CNV candidate list and visualization plots for each sample and gene