Sentence examples for false discovery ratio from inspiring English sources

The reason behind choosing the metric UDR in this paper is explained as follows: in the existing literature, false positive rate or false discovery ratio or false detection ratio (FDR) was used and defined as the ratio of the number of nodes incorrectly identified by the system to the number of nodes actually falling under that group.

False discovery ratio (FDR) ≤0.10 was considered significant.

The false discovery ratio was used to control for the family wise error rate [ 15].

The median false discovery ratio (FDR) cutoff for a multiple class response test by SAM was set to 5%.

Therefore, using the benchmark, statistical filters were optimized to reduce the false discovery ratio, and then remaining motifs from all programs were combined to improve motif prediction.

The threshold values for positively identified genes were as follows: Z-test P-value ≤0.05, the | Z-ratio|≥1.5 and the false discovery ratio ≤0.3.

Mascot score was recalculated by percolator function in the mascot for increasing sensitivity of correct identification and false discovery ratios (FDR) of the search results was adjusted to below 2%.

We applied statistical filters to reduce the false discovery ratios of these programs and then combined the search results to improve motif prediction, and validated this approach using benchmark data.

Size refers to the number of genes in the set; ES and NES are the enrichment scores and normalized enrichment scores (respectively) for the set; NOM p-value is the nominal p-value for the NES, FDR q-vlaue is the false discovery rate ratio (values lower than 0.25 are considered to be passing as per Subramanian et al. [ 4]).

Because we used a limited number of germ-free piglets per time point and measured responses in a mixed population of cells, we imposed stringent criteria for selection of genes (>3.6-fold up- or down-regulation and a false-discovery ratio of less than 5%).

Thus, Fig. 6 shows for this dataset the true positive rate (ratio between true positives and treatment positives, also known as statistical power or sensitivity) and the false discovery rate (FDR, ratio between false positives and detected positives).