Author: Haran Shani-Narkiss; Omri David Gilday; Nadav Yayon; Itamar Daniel Landau
Title: Efficient and Practical Sample Pooling High-Throughput PCR Diagnosis of COVID-19 Document date: 2020_4_7
ID: 6ji8dkkz_24
Snippet: We find for these values of p and b that the average number of tests required to check N samples is about 8 â„ . Meanwhile for p=0.001, the optimal initial batch size is 692, which we round down to = 2 9 = 512 in practice, and find that the average number of tests required to check N samples is about 50 â„ (Figure 1 ). Figure 1 shows that our simulations with batch sizes rounded down to the nearest power of 2, are predicted very well by the two.....
Document: We find for these values of p and b that the average number of tests required to check N samples is about 8 â„ . Meanwhile for p=0.001, the optimal initial batch size is 692, which we round down to = 2 9 = 512 in practice, and find that the average number of tests required to check N samples is about 50 â„ (Figure 1 ). Figure 1 shows that our simulations with batch sizes rounded down to the nearest power of 2, are predicted very well by the two analytical expressions above (i.e. without rounding b).
Search related documents:
Co phrase search for related documents- average number and initial batch size: 1
- average number and optimal initial batch size: 1
- batch size and initial batch size: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
- batch size and optimal initial batch size: 1, 2, 3, 4
- initial batch size and optimal initial batch size: 1, 2, 3, 4
Co phrase search for related documents, hyperlinks ordered by date