[BioC] PCA-3D Plot

James W. MacDonald jmacdon at uw.edu
Mon Jul 1 16:05:47 CEST 2013



On 7/1/2013 8:28 AM, Chevala V V S Narayana [guest] wrote:
> Dear All,
>
> I request help in generating "Sample-based 3D-PCA plot" (Principal component analysis). I used function "princomp" from package:stats to create a PCA object on the data-set. the data dimensions are 600 * 7.
>
> While genetaring, the plot were created on Genes with both "plot3d" and "scatterplot3d" functions, and I want the PCA-3d plot according to the samples.
>
> The code I used is,
>> dim(Expresso)
> [1] 618   7
>> PCA_3d<-princomp(Expresso, cor=TRUE)

Both princomp() and prcomp() expect the data to be in a conventional 
format (with samples in rows and observations in columns). Microarray 
data are in general transposed from this format (with observations in 
rows and samples in columns), so you need to do

princomp(t(Expresso), cor = TRUE)

Best,

Jim


>> plot3d(PCA_3d$scores[,1:7],xlab="Component 1",main="My 3D
> + PCA",ylab="Component 2", zlab="Component 3", type="h", box=F, axes=F)
>> spheres3d(PCA_3d$scores[,1:7], radius=0.1, col="pink")
>> grid3d(side="z", at=list(z=0))
>> text3d(PCA_3d$scores[,1:7], text=rownames(PCA_3d$scores), adj=1.3)
> I also tried to plot with function "scatterplot3d"
>> scatterplot3d(PCA_3d$scores[,1:3],xlab="Component 1 (26.9%)",main="My 3D PCA",ylab="Component 2(17.9%)", zlab="Component 3 (12.4%)",type="h",box=FALSE,pch=21)
>> scatterplot3d(PCA_3d$scores [,1:3],xlab="Component 1 (26.9%)",main="My 3D PCA",ylab="Component 2(17.9%)", zlab="Component 3 (12.4%)",type="h",box=FALSE,pch=21,bg=color)
>
>
>
>
>
>
>   -- output of sessionInfo():
>
>> sessionInfo()
> R version 2.15.1 (2012-06-22)
> Platform: x86_64-redhat-linux-gnu (64-bit)
>
> locale:
>   [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
>   [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
>   [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
>   [7] LC_PAPER=C                 LC_NAME=C
>   [9] LC_ADDRESS=C               LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] ggplot2_0.9.3        reshape2_1.2.2       scatterplot3d_0.3-33
> [4] rgl_0.93.935         DESeq_1.10.1         lattice_0.20-13
> [7] locfit_1.5-8         Biobase_2.18.0       BiocGenerics_0.4.0
>
> loaded via a namespace (and not attached):
>   [1] annotate_1.36.0      AnnotationDbi_1.20.3 colorspace_1.2-1
>   [4] DBI_0.2-5            dichromat_2.0-0      digest_0.6.2
>   [7] genefilter_1.40.0    geneplotter_1.36.0   grid_2.15.1
> [10] gtable_0.1.2         IRanges_1.16.5       labeling_0.1
> [13] MASS_7.3-23          munsell_0.4          parallel_2.15.1
> [16] plyr_1.8             proto_0.3-10         RColorBrewer_1.0-5
> [19] RSQLite_0.11.2       scales_0.2.3         splines_2.15.1
> [22] stats4_2.15.1        stringr_0.6.2        survival_2.37-2
> [25] tcltk_2.15.1         tools_2.15.1         XML_3.95-0.1
> [28] xtable_1.7-0
>
>
> --
> Sent via the guest posting facility at bioconductor.org.
>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099



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