Exact(1)
I believe that there must be a serious error in Dataset 2. Unless I am missing something, the data reported for "starved" and " ad libitum" treatments are identical.
Similar(59)
The average imputation error rate in dataset 2 was 0.41%, which was lower than what was obtained with method C in dataset 1 (0.67%) and in dataset 3 (0.64%).
A significant departure from this ratio could indicate documentation or genotyping errors in datasets [54].
This statistic gives a global characterization of gene diversity and does not reveal sampling biases, such as errors in datasets (e.g. chimeric sequences or taxonomically misclassified isolates) or non-uniform population structures (e.g. the existence of independent genetic lineages within a species).
They show that under the default parameters that wcd is more robust and capable of handling errors in datasets without loss of accuracy.
The presence of error in the dataset, however, does not preclude an analysis using this dataset.
Allelic dropout was a more common form of genotyping error in this dataset than the occurrence of false alleles.
Alternatively, since bin 1 is defined exclusively by six markers of the PstI/ MseI enzyme combination (and does not contain AFLP markers from the other two enzyme combinations in the ultradense genetic map), bin 1 may be an artefact caused by a systematic error in the dataset of this enzyme combination.
As far as we know, none of the previously published human coexpression networks [2], [5], [6] has a comprehensive calculation of the estimated statistical error in the datasets at different levels of coverage.
As we have shown, contaminating adapter sequences account for much of the DRISEE error in Illumina datasets.
> -wrap-foot> There appears to be a significant amount of Type II error in the datasets (Table 3).
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