From these 2,298 samples, for cost-efficiency reasons we selected a subsample for genetic analyses, using a case cohort design.
We investigate this question with CoBRA®,1 a cost estimation method that applies simulation, that is, random sampling, for cost estimation.
For low costs of remote sensing as opposed to per field plot cost (Figure 2A, Figure 3C, Figure 5A,Figure 6C) the design alternatives utilizing remote sensing perform better than SRS, with the exception of stratified sampling for costs below 0.5 US$/ha and regression estimators with r2 = 0.3 for costs below 0.4 US$/ha (Figure 4E, Figure 7E).
For low costs of remote sensing as opposed to per field plot cost the design alternatives utilizing remote sensing perform better than SRS, with the exception of stratified sampling for costs below 0.5 US$/ha and regression estimators with r2 = 0.3 for costs below 0.4 US$/ha.
Wards covering the islands, areas north of the Caledonian Canal, or those with fewer than three urban/suburban Enumeration Districts, were excluded from the sampling frame for cost and practicality reasons.
However, the required sophisticated sample preparation steps and associated costs make that approach currently more attractive for patient samples than for cost-sensitive high-throughput stem cell donor registry typing.
To this end, the objective of this work was to (1) evaluate the accuracy of variation discovery within T-NGS data obtained from matched non-amplified and preamplified WGA HapMap gDNA samples, and (2) test the effect of sample multiplexing for cost- and time-saving reasons, at different stages of the sequencing workflow, on key enrichment metrics.
For 96 samples, the cost simply for purification of each of these samples individually three times (288 purifications, as per the post-capture TGE method) is $1,658.88.
In the derivation sample for formal costs alone, only two groups show CV values higher than the overall CV, namely, groups 3 and 7.
