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Factominer

Manufactured by Posit
Sourced in United States

FactoMineR is a multivariate data analysis software package for the R programming language. It provides tools for principal component analysis, hierarchical clustering, and multiple correspondence analysis. FactoMineR is designed to facilitate the exploration and visualization of complex datasets.

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Lab products found in correlation

2 protocols using factominer

1

Comprehensive Analysis of Sunflower Oil

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The Tukey test was used to test the contrasts between the treatment means (extraction methods and plant matrices) and to verify whether there was a difference between the treatments (SFO, SFO + OLE, and OLE) concerning oxidative stability, antioxidant activity, FAs, and IT, using SISVAR software version 5.7 (Ferreira, 2014 (link)).
Mass percentage yield results were submitted to t-student test at 5% significance using Statistica software, version 8.0 for each group of samples in each analysis. Values followed by different letters indicate significant differences.
The multivariate method of principal component analysis (PCA) was used to reduce the number of variables and to evaluate the contribution of the FAs and active compounds in the SFO, SFO + OLE, and OLE, using the computational package FactoMineR (R Studio Inc., Boston, MA, USA) (Luo et al., 2009 (link)).
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2

Principal Component Analysis of COVID-19 Symptoms

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Unsupervised principal components analyses (PCA) were performed in R Studio. Complete data were scaled to variance units using FactoMineR (v2.4 R studio) and the PCA results were extracted and visualized using factoextra (v1.0.7 R Studio). For Figures 2, 3, the PCA was performed using all samples data and graphed by days from the onset of symptoms (Early ≤ 43 days; Late > 43 days) for Figure 2 or by the severity of symptoms (mild or more severe) for Figure 3. In Figures 4, 5 the data was divided into two subgroups by the days from the onset of symptoms criteria and then the PCA was performed using severity of symptoms for Figure 4 or sex for Figure 5.
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