Skip to main content
Fig. 3 | Genome Medicine

Fig. 3

From: Combinatorial batching of DNA for ultralow-cost detection of pathogenic variants

Fig. 3

Illustrates scalability and estimated economic impact of lowered price per sample (PPS). A The PPS stratified by the size of the matrix, with line colors corresponding to those of the text and matrices in panel B. The x-axis represents sequencing yield in the targeted area, under a conservative assumption of 50% quality control data loss. The logarithmic y-axis shows the raw estimated price of sequencing the samples from a single individual. The dots represent empirical data from single batched sequencing at the specified batch sizes, including the sensitivity for loss-of-function and/or known pathogenic (LoF/P) variant detection. B Population size and number of tests needed to screen every individual using the double batched sequencing (DoBSeq) method. C The price per diagnosis (PPD, i.e., LoF/P variant detection) as influenced by PPS for 11 selected childhood cancer predisposition syndrome (CPS) genes corresponding to those investigated by Yeh et. al .[16], as well as all 11 genes combined. Legend is ordered by CPS prevalence. Prevalence is based on the best available evidence. D Based on the economic model by Yeh et al .[16] this graph illustrates the cost per quality-adjusted life-year (QALY) gained by tumor surveillance (within the 11 CPSs in panel C) at decreasing PPS. The dotted lines delineate screening costs that are cost-prohibitive, cost-effective at a liberal cut-off of $100k per QALY, and cost-effective at a conservative cut-off of $50k per QALY, respectively. Colored dots correspond to PPS at selected matrix sizes (see panel B)

Back to article page