r - Different Valuse Returned from Using PCA Function -

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can explain me how these different?

#first type of pca.  scales , transposes manually pr.data <- prcomp(scale(t(data)))  #second type of pca pr.data <- prcomp(data, retx=true, scale=true)

is 1 transposed (the first one) , second 1 not transposed?

i think t(data) affect data because switch positions of "samples vs. features" "features vs. samples." transposing matrix "flip" analysis.


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