ASCA.GetSummary: Summary method for ASCA analyses

In MetStaT: Statistical metabolomics tools

Description

Returns a matrix which contains a summary of the ASCA results. Each row in the matrix contains results for one factor or interaction studied in the performed ASCA. The columns contain the relevant principal components (PC's) found and the amount of variance explained per PC. A max of 10 PC's are shown, and only those PC's which explain more than 1% of the variance.

Usage

ASCA.GetSummary(asca, quietly = FALSE)

Arguments

asca	The result of an already performed ASCA by ASCA.Calculate
quietly	boolean. If TRUE the method will not print the table of results, but only return the matrix containing the results. Defaults to FALSE.

Value

summary

A matrix containing the variance explained per component per factor or interaction.

Note

Output of ASCA.Calculate is required.

Author(s)

Tim Dorscheidt

Examples

## load the example data
data(ASCAdata)

## Do ASCA on all (both) factors and the interaction between the two factors
ASCA <- ASCA.Calculate(ASCAX, ASCAF, equation.elements = "1,2,12", scaling = TRUE)

## Get a summary of the ASCA results
ASCA.GetSummary(ASCA)

Example output

Loading required package: MASS
Loading required package: abind
Loading required package: pls

Attaching package: 'pls'

The following object is masked from 'package:stats':

    loadings

Variance explained per principal component (if >1%):
Whole data set 	PC1: 52.84%   PC2: 22.89%   PC3: 18.92%   PC4: 5.34%    
Factor 1     	PC1: 100.00%  PC2:  NA%     PC3:  NA%     PC4:  NA%     
Factor 2     	PC1: 91.34%   PC2: 8.66%    PC3:  NA%     PC4:  NA%     
Interaction 12	PC1: 88.72%   PC2: 11.28%   PC3:  NA%     PC4:  NA%     

Percentage each effect contributes to the total sum of squares:
Overall means  	0.96%
Factor 1     	0.00%
Factor 2     	0.00%
Interaction 12	0.00%
Residuals      	0.00%

Percentage each effect contributes to the sum of squares of the centered data:
Factor 1     	0.00%
Factor 2     	0.00%
Interaction 12	0.00%
Residuals      	0.00%

Variance explained per principal component (if >1%):
Whole data set 	PC1: 52.84%   PC2: 22.89%   PC3: 18.92%   PC4: 5.34%    
Factor 1     	PC1: 100.00%  PC2:  NA%     PC3:  NA%     PC4:  NA%     
Factor 2     	PC1: 91.34%   PC2: 8.66%    PC3:  NA%     PC4:  NA%     
Interaction 12	PC1: 88.72%   PC2: 11.28%   PC3:  NA%     PC4:  NA%     

Percentage each effect contributes to the total sum of squares:
Overall means  	0.96%
Factor 1     	0.00%
Factor 2     	0.00%
Interaction 12	0.00%
Residuals      	0.00%

Percentage each effect contributes to the sum of squares of the centered data:
Factor 1     	0.00%
Factor 2     	0.00%
Interaction 12	0.00%
Residuals      	0.00%

$summary.pca
           PC1        PC2      PC3        PC4
data 0.5284457 0.22893154 0.189173 0.05344977
1    1.0000000         NA       NA         NA
2    0.9133702 0.08662983       NA         NA
12   0.8871602 0.11283977       NA         NA

$summary.ssq
                    Overall means            1            2           12
Contribution to ssq   0.009555144 2.465465e-05 1.609305e-05 7.348948e-06
                       Residuals
Contribution to ssq 3.198811e-05

MetStaT documentation built on May 2, 2019, 1:45 p.m.