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For each functional category of genes we utilized a False Discovery Rate (FDR) of ≤0.01 to assess the impact of multiple testing.
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Utilizing a false discovery rate calculation limits the possibility of false positives due to chance alone.
Utilizing a false discovery rate of <0.05, we found that 2126 genes were differentially regulated in AD hippocampal neurons compared to controls when combining the two studies (Additional file 1: Table S1).
Identification of genes displaying a change in expression over repetitions was accomplished with a script utilizing library functions in R with a false discovery rate (FDR) of less than 5%.
To identify genes displaying a change in expression over repetitions, a script utilizing library functions in R with a false discovery rate (FDR) of less than 5% was used for all experimental conditions.
To correct for multiple comparisons in these analyses, a False Discovery Rate (FDR) method was utilized [ 19, 20], and is reported along with the results.
A false discovery rate approach [ 26] was utilized to deal with the major issue of multiple testing.
Student's t-tests, and a false discovery rate (FDR) threshold of 0.2, were utilized to identify upregulated proteins between the PsA and PsC lesional groups (PsA L, and PsC L, respectively).
A p-value cut-off of 0.01 and a false discovery rate (FDR) cut-off of 0.05 were utilized to determine statistical significance of each SNP.
To control false positive discovery rate we apply Benjamini-Hochberg correction: ∗represent Benjamini-Hochberg critical value with a false discovery rate of 0.2; and the rest of points - critical value for a false discovery rate of 0.1.
Of these, 3 effects were significant at P < 0.01, for a false discovery rate of 0.24.
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CEO of Professional Science Editing for Scientists @ prosciediting.com