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SIS said it had determined the error was unintentional.
We generated short-read sequences on a Solexa/Illumina GA I genome analyser and determined the error distribution.
With this dataset, we determined the error bars in Figure 3 using 5-fold cross-validation with a prior random reshuffling of the sample order.
From measurements in which all 96 wells were inoculated with wild-type MG1655, we determined the error margins on our averaged growth data to be 4.3%.
For the scenarios with the dichotomous outcome we determined the error rate when the OR was evaluated (logistic model) and when the RR was estimated.
To obtain a robust estimate of the base-substitution error frequency across the 2-kb interval sequenced, we combined the CCS reads from hundreds of independent Can-R mutants isolated under low-transcription conditions and determined the error frequency at each position.
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UPDATE: I received an email from Michael Robertson…Oboe is trying to determine the error.
The diversity order is one of the most important parameters determining the error rate.
For two coordinates, and with measured values, we can determine the error in position measurement as.
If (Delta t_{mathrm{soft}}/r_{mathrm{cut}} sigma) is large, it determines the error.
For each robot, a coordinate transformation is first derived to determine the error in the system.
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