simulation_Ic_sample {BioTIP} | R Documentation |
Run B
times of sample-label shuffling to calculate the Ic score,
where x should be the same as the length of identified BioTiP and B is self-defined.
simulation_Ic_sample( counts, sampleNo, Ic = NULL, genes, B = 1000, ylim = NULL, main = "simulation of samples", fun = c("cor", "BioTIP"), shrink = TRUE, use = c("everything", "all.obs", "complete.obs", "na.or.complete", "pairwise.complete.obs"), output = c("Ic", "PCCg", "PCCs"), plot = FALSE )
counts |
A numeric matrix or data frame. The rows and columns represent unique transcript IDs (geneID) and sample names, respectively. |
sampleNo |
An integer of sample size at the tipping-point state. |
Ic |
A numeric value. Ic score of identified CTS (gene-set), useful when |
genes |
A character vector of identified CTS gene unique ids. |
B |
An integer indicating number of times to run this simulation, default 1000. |
ylim |
An integer vector of length 2. Default is NULL. |
main |
A character vector. The title of the plot. Default is NULL. |
fun |
An optional character string indicating the R functon to calculate correlations
for all possible pairs of columns of a matrix.
When using "BioTIP", The method is modified to ignore missing values, analogous to how
|
shrink |
A flag specifying whether to shrink the correlation or not.
This appraoch uses the method outlined by Schafer and Strimmer in
"A Shrinkage Approach to Large-Scale Covariance Matrix Estimation
and Implications for Functional Genomics" (2005)
Comparing to fun='cor', the 'BioTIP' method without shinkage is modified
to ignore missing values, analogous to how |
use |
An optional character string, when fun=="cor", it gives a method for computing covariances in the presence of missing values. This must be (an abbreviation of) one of the strings "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs". |
output |
A string. Please select from 'Ic', 'PCCg', or 'PCCs'. Uses 'Ic' by default. 'PCCg' is the PCC between genes (numerator) and 'PCCs' is PCC between samples (denominator) |
plot |
A Bollen value indicating whether a density plot will be plotted. |
A vector of B
values of BioTIP (or Ic) scores calculated for the state of interest.
Zhezhen Wang zhezhen@uchicago.edu; Xinan H Yang xyang2@uchicago.edu
counts = matrix(sample(1:100, 27), 3, 9) colnames(counts) = 1:9 row.names(counts) = c('loci1', 'loci2', 'loci3') CTS = c('loci1', 'loci2') randomS <- simulation_Ic_sample(counts, sampleNo=3, Ic=3.4, genes=CTS, B=3, fun='BioTIP', plot=TRUE) dim(randomS)