Description Usage Arguments Details Value Author(s) References Examples
This function simulates a two-group comparison microarray data set according to a hierarchical model, where the standardized effect sizes across all genes are assumed to be independently and identically distributed. This distribution is a two-component mixture. It has probability pi0 of being zero; and probability 1-pi0 of being from another distribution. The observed values are simulated independently conditional on the standardized effect sizes.
1 2 3 |
G |
a numeric positive integer, the number of genes |
pi0 |
a numeric value between 0 and 1, the proportion of non-differentially expressed genes. |
gamma2 |
a positive value, which is always the second argument passed to |
n1 |
a positive integer, the sample size in treatment group 1. |
n2 |
a positive integer, the sample size in treatment group 2. |
errdist |
a function, which simulate |
effdist |
a function, which simulate |
ErrArgs |
a list of additional arguments used by |
EffArgs |
a list of additional arguments used by |
The funciton simulates G*N errors according to errdist
, where N=n1+n2. The results
are organized into a G-by-N matrix. The G1 standarized effect sizes are simulated according to
effdist
, controlled by the parameter gamma2
, where \code{G1=round(G*pi0)}.
Then, each column of the upper-left G1-by-n1 submatrix were added by the simulated effect sizes.
a G
-by-(n1+n2)
matrix.
Long Qu
Qu, L., Nettleton, D., Dekkers, J.C.M. Subsampling Based Bias Reduction in Estimating the Proportion of Differentially Expressed Genes from Microarray Data. Unpublished manuscript.
1 2 3 4 5 6 7 | set.seed(54457704)
## an unusually small data set of 20 genes and 3 samples in each of the two treatment groups.
dat=sim.dat(G=20, n1=3,n2=3)
set.seed(9992722)
## this is how the 'simulatedDat' data set in this package generated
simulatedDat=sim.dat(G=5000)
|
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