The PCA results of the demo 1KG reference dataset for demonstration purpose. Beware that the PCA has been run on a very small subset of the 1KG reference dataset and should not be used to call ancestry inference on a real profile.

Source: R/RAIDS.R

The object is a list.

data(demoPCA1KG)

Format

The list containing the PCA results for a small subset of the reference 1KG dataset. The list contains 2 entries:

pruned

a vector of SNV identifiers specifying selected SNVs for the PCA analysis.

pca.unrel

a snpgdsPCAClass object containing the eigenvalues as generated by snpgdsPCA function.

Value

The list containing the PCA results for a small subset of the reference 1KG dataset. The list contains 2 entries:

pruned

a vector of SNV identifiers specifying selected SNVs for the PCA analysis.

pca.unrel

a snpgdsPCAClass object containing the eigenvalues as generated by snpgdsPCA function.

Details

This object can be used to test the computePCAMultiSynthetic function.

Examples


## Required library
library(gdsfmt)

## Loading demo PCA on subset of 1KG reference dataset
data(demoPCA1KG)

## Path to the demo Profile GDS file is located in this package
dataDir <- system.file("extdata/demoKNNSynthetic", package="RAIDS")

# The name of the synthetic study
studyID <- "MYDATA.Synthetic"

samplesRM <- c("HG00246", "HG00325", "HG00611", "HG01173", "HG02165",
    "HG01112", "HG01615", "HG01968", "HG02658", "HG01850", "HG02013",
    "HG02465", "HG02974", "HG03814", "HG03445", "HG03689", "HG03789",
    "NA12751", "NA19107", "NA18548", "NA19075", "NA19475", "NA19712",
    "NA19731", "NA20528", "NA20908")
names(samplesRM) <- c("GBR", "FIN", "CHS","PUR", "CDX", "CLM", "IBS",
    "PEL", "PJL", "KHV", "ACB", "GWD", "ESN", "BEB", "MSL", "STU", "ITU",
    "CEU", "YRI", "CHB", "JPT", "LWK", "ASW", "MXL", "TSI", "GIH")

## Open the Profile GDS file
gdsProfile <- snpgdsOpen(file.path(dataDir, "ex1.gds"))

## Projects synthetic profiles on demo 1KG PCA
results <- computePCAMultiSynthetic(gdsProfile=gdsProfile,
    listPCA=demoPCA1KG, sampleRef=samplesRM, studyIDSyn=studyID,
    verbose=FALSE)

## The eigenvectors for the synthetic profiles
head(results$eigenvector)
#>                       [,1]         [,2]         [,3]         [,4]         [,5]
#> 1.ex1.HG00246.1 0.06469191 -0.004653002 -0.088967175 -0.060291452  0.031812132
#> 1.ex1.HG00325.1 0.09115431 -0.004743912 -0.071907454  0.044100229 -0.041522503
#> 1.ex1.HG00611.1 0.01381479 -0.017912275  0.062489822  0.003760931  0.061062765
#> 1.ex1.HG01173.1 0.02193600  0.016635981 -0.123902643 -0.104948054  0.021495661
#> 1.ex1.HG02165.1 0.15626481 -0.003083060 -0.004768404  0.100910618 -0.002478422
#> 1.ex1.HG01112.1 0.07699686 -0.015195235 -0.102489655 -0.088759431 -0.031143964
#>                         [,6]         [,7]        [,8]        [,9]        [,10]
#> 1.ex1.HG00246.1 -0.087084898 -0.002319659 -0.01327109 -0.06600164  0.011422042
#> 1.ex1.HG00325.1  0.092420817 -0.150333993  0.04064972  0.06185469  0.045882592
#> 1.ex1.HG00611.1  0.006946086  0.037328105  0.01327867 -0.03629313  0.015773551
#> 1.ex1.HG01173.1  0.026114397 -0.045510755 -0.02727912  0.12362088  0.005003337
#> 1.ex1.HG02165.1 -0.213193715 -0.205975416 -0.33167160  0.01689627  0.415307845
#> 1.ex1.HG01112.1  0.140457360 -0.129621812  0.18058981  0.09950699 -0.058262338
#>                         [,11]        [,12]       [,13]       [,14]       [,15]
#> 1.ex1.HG00246.1  0.1135730541  0.120776205  0.05104489  0.10009894  0.08226945
#> 1.ex1.HG00325.1 -0.0213545024  0.017612760 -0.12065696  0.11956275 -0.05519839
#> 1.ex1.HG00611.1  0.0002207075  0.008803511  0.06544166  0.02462076  0.00500031
#> 1.ex1.HG01173.1 -0.0877004088 -0.023906580 -0.11278874 -0.02636037 -0.09290133
#> 1.ex1.HG02165.1  0.1492485496 -0.094433444 -0.10994232  0.06307073  0.06593791
#> 1.ex1.HG01112.1 -0.1773609745 -0.105883583 -0.15020718  0.04382861 -0.04644355

## Close Profile GDS file (important)
closefn.gds(gdsProfile)