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Differentially expressed genes were identified using a random variance ANOVA test.
Differentially expressed miRNAs were selected using a random variance t-test p value less than 0.05 and an absolute fold change greater than 1.2.
Differentially expressed genes were identified from paired comparisons of the three treatment groups (DS vs. WW, DR vs. WW, DR vs. DS) using a random variance test [ 47].
Median normalization of raw expression data and identification of differentially expressed genes using a random variance t-test was performed using BRB-ArrayTools [ 39] version 4.1.0 Beta 2 Release (developed by Dr. Richard Simon and BRBArrayTools Development Team members).
Exercise response genes were evaluated using a random variance t test in a paired, class comparison analysis of control subjects before and after exercise, and 21 genes were identified as being differentially expressed (Table 2).
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All tests involving gene expression data used a random variance model [ 38].
Due to small sample population for each platform we used a random variance model for the univariate tests when distribution assumptions underlying this model were met [41].
To test for genes that were differentially expressed in cell lines with and without benzo[ a]pyrene treatment, we used a random variance t-test as described by Wright et al. [ 20].
Genes that were differentially expressed among classes were identified using a random-variance t-test.
miRNAs that are differentially expressed between breast cancer and gynecomastia were identified using a random-variance t test.
The probability of genes being differentially expressed among the classes was computed using a random-variance t-test.
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