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To identify statistically significant DEGs under drought stress, we used the combined criteria of five-fold or more change and significant t test of P value of less than 0.05 based on three biological replicates.
For each array, the miRNA probe set signals were compared with the distribution of signals for anti-genomic probes that had matching GC content (miRNA QC Tool, version 1.0.33.0), and in accordance with the recommendation of the manufacturer, Wilcoxon rank-sum test of P value of less than 0.06 was used to identify miRNAs above background.
As there is no fixed standard threshold between significant and non-significant differential gene expressions, we identified the DEGs using the empirical criteria of more than five-fold change and significant t test of P value less than 0.05 based on three independent biological replicates.
We suggest incorporating a global test of p-values to filtration procedures to identify the optimal number of genes/SNPs for further MDR analysis and demonstrate this approach using a ReliefF filter technique.
BiNGO [ 36] was used to perform hypergeometric statistical test of significance (p-value < 0.05) to assess GO term enrichment.
The entire procedure of filtration and global testing of p-values are summarized in Table 2.
To circumvent this limitation, we incorporated global testing of p-values and ReliefF algorithm using the method proposed in Section Combined global testing and filtration technique.
Our further simulation studies (discussed in Section Power simulation) indicate that Tippett's test, which only takes the smallest p-value into account, might not be appropriate for global testing of p-values.
This can have a profound impact on testing procedures, especially those that rely on multiple test adjustment of p-values across many genes [ 57].
Lastly, multiple test correction of p-values was done using the false discovery rate (FDR) method [82].
The multiple-test correction of p-values was performed by q-value.
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