MArrayLMobject output from
treatfrom which the t-statistics may be extracted.
"nestedF"or any partial string.
TestResults. This is essentially a numeric matrix with elements
1depending on whether each t-statistic is classified as significantly negative, not significant or significantly positive respectively.If
lfc>0then contrasts are judged significant only when the log2-fold change is at least this large in absolute value. For example, one might choose
lfc=log2(1.5)to restrict to 50% changes or
lfc=1for 2-fold changes. In this case, contrasts must satisfy both the p-value and the fold-change cutoff to be judged significant.
tstatcorrespond to genes and columns to coefficients or contrasts.
method="separate" is equivalent to using
topTable separately for each coefficient in the linear model fit, and will give the same lists of probes if
adjust.method is the same.
method="global" will treat the entire matrix of t-statistics as a single vector of unrelated tests.
method="hierarchical" adjusts down genes and then across contrasts.
method="nestedF" adjusts down genes and then uses
classifyTestsF to classify contrasts as significant or not for the selected genes.
Please see the limma User's Guide for a discussion of the statistical properties of these methods.