Hi
I am analysing a dataset of 40 samples each with 90,000 intensity measures for
various peptides. I am trying to identify the Biomarkers (i.e. most significant
peptides). I beleive that PLS with jack knifing, or alternativeley
CMV(cross-model-validation) are multivariateThe 40 samples belong to four
different groups.
I have managed to conduct the plsr using the commands:
BHPLS1 <- plsr(GroupingList ~ PCIList, ncomp = 10, data = PLSdata, validation =
"LOO")
and
BHPLS1 <- plsr(GroupingList ~ PCIList, ncomp = 10, data = PLSdata, validation =
"CV")
I have also used the following command to obtain the loadings
BHPLS1_Loadings <- loadings(BHPLS1)
Now I am unsure of how to utilise these to identify the significant variables.
Do I need to use any loops?
str(BHPLS1_Loadings)
loadings [1:94727, 1:10] -0.00113 -0.03001 -0.00059 -0.00734 -0.02969 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:94727] "PCIList1" "PCIList2" "PCIList3" "PCIList4" ...
..$ : chr [1:10] "Comp 1" "Comp 2" "Comp 3" "Comp 4" ...
- attr(*, "explvar")= Named num [1:10] 14.57 6.62 7.59 5.91 3.26 ...
..- attr(*, "names")= chr [1:10] "Comp 1" "Comp 2" "Comp 3" "Comp 4" ...
Many thanks in advance
AK
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