Hi John In made4, For correspondence analysis (COA, the default option
in made4) the total $eig will be equivalent to the total chi-sq of the
table. data.coa <- ord(eSetdata, type = "coa") To get the % of variance
explained by each axis. > data.coa$ord$eig * 100/sum(data.coa$ord$eig)
[1] 33.69 23.13 12.65 9.84 6.44 5.83 4.66 3.76 The cumulative variance
is given by > cumsum(data.coa$ord$eig * 100/sum(data.coa$ord$eig)) [1]
33.7 56.8 69.5 79.3 85.7 91.6 96.2 100.0 Therefore almost 57% of the
variance is captured by the first 2 components.

For PCA

 data.pca <- ord(eSetdata, type = "pca")


  To get the % of variance explained by each axis.

   data.pca$ord$eig * 100


  The cumulative variance is given by

  cumsum(data.coa$ord$eig * 100)

Examples of these and more complete explanation are given on the website
http://compbio.dfci.harvard.edu/courses/bioconductor/ with the vignette
url http://compbio.dfci.harvard.edu/courses/bioconductor/MGED_Oct09.pdf
best regards Aedin Message: 7 Date: Mon, 18 Oct 2010 11:53:40 +0200
From: "Gerhard Thallinger" <Gerhard.Thallinger@tugraz.at> To: "'John
Antony Gaspar'" <gasparj@uni-koeln.de> Cc:
bioconductor@stat.math.ethz.ch Subject: Re: [BioC] Percentage of
Variance to be included at 3D graph of Principal Component Analysis
(PCA)- made4 package Message-ID:
<A1317A5FAE314443AF5958A387E95419@AGILIX> Content-Type: text/plain;
charset="us-ascii" Dear John,

> > Please help me out with this regard. 'prcomp' provides Standard 
> > deviation, Proportion of variance and Cumulative Proportion. How to 
> > use them in calculating the percentage of variance at all three 
> > PC level.
>   

  The percentage of variance explained can be calculated as follows:

    pca <- prcomp(USArrests, scale = TRUE)
    pc1 <- round(pca$sdev[1]2/sum(pca$sdev2)*100,2)
    pc2 <- round(pca$sdev[2]2/sum(pca$sdev2)*100,2)
    etc ...

Hth 

Gerhard

------------------------------------------------------------------------
Dr. Gerhard Thallinger             E-mail:  Gerhard.Thallinger@tugraz.at
Institute for Genomics and Bioinformatics   Web: http://genome.tugraz.at
Graz University of Technology               Tel:        +43 316 873 5343
Petersgasse 14/V                            Fax:      +43 316 873 105343
8010 Graz, Austria                 Map: http://genome.tugraz.at/Loc.html

-- 
Aedín Culhane,
Computational Biology and Functional Genomics
Harvard School of Public Health, Dana-Farber Cancer Institute

44 Binney Street, SM822C
Department of Biostatistics and Computational Biology,
Dana-Farber Cancer Institute
Boston, MA 02115
USA

Phone: +1 (617) 632 2468
Fax:   +1 (617) 582 7760
Email: aedin@jimmy.harvard.edu
Web URL: http://www.hsph.harvard.edu/research/aedin-culhane/



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