A simulated dataset to show the utility of this package
admixed
An object of class list of length 21.
A list with the following elements
simulated response vector for tuning parameter selection set
simulated response vector for test set
simulated design matrix for training set
simulated design matrix for tuning parameter selection set
simulated design matrix for testing set
simulated design matrix for training set for lasso model. This is the same as xtrain, but also includes the nPC principal components
simulated design matrix for tuning parameter selection set for lasso model. This is the same as xtune, but also includes the nPC principal components
simulated design matrix for testing set for lasso model. This is the same as xtest, but also includes the nPC principal components
character vector of the names of the causal SNPs
the vector of true regression coefficients
2 times the estimated kinship for the training set individuals
The covariance matrix between the tuning set and the training set individuals
The covariance matrix between the test set and training set individuals
the matrix of SNPs used to estimate the kinship matrix
character vector of the non-causal SNPs
the principal components for population structure adjustment
The code used to simulate the data is available at
https://github.com/sahirbhatnagar/ggmix/blob/master/data-raw/bnpsd-data.R.
See gen_structured_model for more details on the output and
how the function used to simulate the data.
Ochoa, Alejandro, and John D. Storey. 2016a. "FST And Kinship for Arbitrary Population Structures I: Generalized Definitions." bioRxiv doi:10.1101/083915.
Ochoa, Alejandro, and John D. Storey. 2016b. "FST And Kinship for Arbitrary Population Structures II: Method of Moments Estimators." bioRxiv doi:10.1101/083923.
#> List of 21 #> $ ytrain : Named num [1:80] 1.78783 -0.00688 -0.66998 -1.6918 -0.22518 ... #> ..- attr(*, "names")= chr [1:80] "id1" "id2" "id3" "id4" ... #> $ ytune : Named num [1:10] -3.337 -1.642 -0.494 2.487 2.57 ... #> ..- attr(*, "names")= chr [1:10] "id21" "id25" "id28" "id49" ... #> $ ytest : Named num [1:10] 3.123 -0.244 -1.608 -1.396 1.077 ... #> ..- attr(*, "names")= chr [1:10] "id26" "id39" "id45" "id52" ... #> $ xtrain : int [1:80, 1:50] 0 0 1 0 2 2 0 0 0 0 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> .. ..$ : chr [1:50] "X23" "X36" "X38" "X40" ... #> $ xtune : int [1:10, 1:50] 0 0 1 1 1 1 1 1 0 1 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:10] "id21" "id25" "id28" "id49" ... #> .. ..$ : chr [1:50] "X23" "X36" "X38" "X40" ... #> $ xtest : int [1:10, 1:50] 0 1 1 1 1 1 2 0 2 2 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:10] "id26" "id39" "id45" "id52" ... #> .. ..$ : chr [1:50] "X23" "X36" "X38" "X40" ... #> $ xtrain_lasso : num [1:80, 1:60] 0 0 1 0 2 2 0 0 0 0 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> .. ..$ : chr [1:60] "X23" "X36" "X38" "X40" ... #> $ xtune_lasso : num [1:10, 1:60] 0 0 1 1 1 1 1 1 0 1 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:10] "id21" "id25" "id28" "id49" ... #> .. ..$ : chr [1:60] "X23" "X36" "X38" "X40" ... #> $ xtest_lasso : num [1:10, 1:60] 0 1 1 1 1 1 2 0 2 2 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:10] "id26" "id39" "id45" "id52" ... #> .. ..$ : chr [1:60] "X23" "X36" "X38" "X40" ... #> $ Xkinship : int [1:80, 1:500] 0 0 0 0 0 0 0 0 0 0 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> .. ..$ : chr [1:500] "X279" "X295" "X346" "X304" ... #> $ kin_train : num [1:80, 1:80] 1.0303 0.0722 0.0664 0.0315 0.1244 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> $ kin_tune_train: num [1:10, 1:80] 0.08378 0.03152 0.00248 -0.02074 0.00829 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:10] "id21" "id25" "id28" "id49" ... #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> $ kin_test_train: num [1:10, 1:80] 0.078 0.0257 0.1244 0.0664 -0.0324 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:10] "id26" "id39" "id45" "id52" ... #> .. ..$ : chr [1:80] "id1" "id2" "id3" "id4" ... #> $ mu_train : num [1:80] 1.81 1.84 -1.45 -1.24 0.86 ... #> $ causal : chr [1:5] "X407" "X507" "X524" "X538" ... #> $ beta : num [1:50] 0 0 0 0 0 0 0 0 0 0 ... #> $ not_causal : chr [1:45] "X23" "X36" "X38" "X40" ... #> $ kinship : num [1:100, 1:100] 0.5281 0.0557 0.0553 0.0549 0.0544 ... #> $ coancestry : num [1:100, 1:100] 0.0561 0.0557 0.0553 0.0549 0.0544 ... #> $ PC : num [1:100, 1:10] 0.855 -1.15 -0.514 -0.443 -1.219 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:100] "id1" "id2" "id3" "id4" ... #> .. ..$ : chr [1:10] "PC1" "PC2" "PC3" "PC4" ... #> $ subpops : num [1:100] 1 1 1 1 1 1 1 1 1 1 ...