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Principal component analysis (using the prcomp function with scale = T) and cluster analysis was performed on the dataset of 259 compounds with 86 CDK descriptors using R.
Principal Component Analysis (PCA) was applied using the prcomp function in R stats package with default parameters except that the center parameter was set to FALSE.
Principal component analysis was performed using the prcomp function.
Calculations were performed in R using the prcomp function.
Principal Component Analysis was performed on these matrices using the prcomp function.
Principal components analysis was performed using the prcomp function with default parameters.
Similar(40)
For the figures showing principal component analysis, we used the prcomp function in R. We used DAVID functional annotation tool for a Gene Ontology enrichment analysis [ 42, 43], taking one term from each cluster in the output and requiring a 5%% Benjamini-adjusted p-value produced by DAVID.
We used the prcomp function in R to perform the PCA.
PCA was performed using the prcomp R function with default parameters.
A subtlety that affects the numerical accuracy of calculations is the divisor N used for the covariance matrix in the princomp function (an EVD-based PCA implementation) and the divisor N−1 used in the prcomp function (an SVD implementation) [17].
A Principal Component Analysis (PCA) was performed using the prcomp command in R version 3.2.3.
More suggestions(15)
using the lm function
using the histogram function
using the prcomp command
using the repair function
using the despeckle function
using the search function
using the likelihood function
using the duleg function
using the share function
using the prcomp module
using the image function
using the calibrate function
using the Trace function
using the ruler function
using the table function
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