Hi, I try to reproduce the results produced by lefse. I am a little bit confused about how to produce the scores of LDA in lefse procedure.
The original paper described the LDA step: An LDA model is finally built with the class as dependent variable and the remaining feature values, subclass, and subject values as independent variables. This model is used to estimate their effect sizes, which are obtained by averaging the differences between class means (using unmodified feature values) with the differences between class means along the first linear discriminant axis, which equally weights features’ variability and discriminatory power. The LDA score for each biomarker is obtained computing the logarithm (base 10) of this value after being scaled in the [1,10^6] interval and, regardless of the absolute values of the LDA score, it induces the ranking of biomarker relevance. For robustness, LDA is additionally supported by bootstrapping (default 30-fold) and subsequent averaging.
I am really confused? So the Lefse LDA score is not the regular LDA score right? Then how to compute it?