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In addition to recording qualitative specificity profiles, data provided by the system can be analyzed quantitatively, yielding specificity constant values.
The regulatory sequences that play a role in the qualitative specificity of gene expression have been intensely studied.
For BacCow and BacHum the 25th/75th metrics were 0.4 and 0.7 log units, respectively; for BacR it was larger than 1.6 log units, giving BacR not only the highest qualitative specificity but also the clearest separation of false-positive and true-positive signals.
For example it becomes even more evident that although BoBac might have similar numbers of false-positives as the BacCow assay (qualitative specificity) the concentrations of BoBac in false-positive nontarget samples are much higher than those of BacCow (quantitative specificity).
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BacR showed the highest qualitative specificities in most subgroups with some false-positives from dog samples.
The ruminant-targeted assays BacCow and BoBac showed qualitative specificities of 57% and 59%, respectively, while the specificity of the BacR assay was higher at 84%.
BoBac had the lowest levels of qualitative source-specificity of all assays in the subgroups of carnivores and birds.
The qualitative source-specificities of the human-targeted assays were 53% for BacH and 68% for BacHum (Table 1).
Qualitative source-specificity was defined as the percentage of nontarget samples not detected by qPCR (all signals <1 copy per reaction; true-negatives) (Table 1).
Interestingly, the qualitative source-specificities determined in this study were found to be consistently lower than those reported in the original publications, conducted at a local or regional level.
Although qualitative source-specificity and -sensitivity provide a general indication of assay performance based on the presence/absence of specific markers, they give no information concerning the relative abundance of those markers in such sources.
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