simulation_Ic: Calculating random Index of Critical transition (Ic scores)...

In xyang2uchicago/NPS: BioTIP: An R package for characterization of Biological Tipping-Point

Calculating random Index of Critical transition (Ic scores) for randomly-selectd genes

Description

Simulating Ic scores for x randomly selected samples, where x should be the same as the length of identified critical-transition signal (CTS) (e.g., number of genes) and B is self-defined running times.

Usage

simulation_Ic(
  obs.x,
  sampleL,
  counts,
  B = 1000,
  fun = c("cor", "BioTIP"),
  shrink = TRUE,
  use = c("everything", "all.obs", "complete.obs", "na.or.complete",
    "pairwise.complete.obs"),
  output = c("Ic", "PCCg", "PCCs")
)

Arguments

obs.x	An integer, length of identified CTS.
sampleL	A list of vectors, whose length is the number of states. Each vector gives the sample names in a state. Note that the vector s (sample names) has to be among the column names of the R object 'df'.
counts	A numeric matrix or dataframe in which columns are samples and rows are transcripts. Each row needs to have a unique row name (i.e. transcript ID).
B	An integer, setting the permutation with B runs. Default is 1000.
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 cor(X, use = "pairwise.complete.obs") works. Note that the "BioTIP" option only function together with shrink = TRUE.
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 cor(X, use = "pairwise.complete.obs") works.
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)

Value

A matrix of y rows and B columns where y is the length of sampleL and B is self-defined. Each column is a set of Ic scores calculated for each state

Author(s)

Zhezhen Wang [e-mail]

Examples

counts = matrix(sample(1:100, 27), 3, 9)
colnames(counts) = 1:9
row.names(counts) = c('loci1', 'loci2', 'loci3')
cli = cbind(1:9, rep(c('state1', 'state2', 'state3'), each = 3))
colnames(cli) = c('samples', 'group')
samplesL <- split(cli[, 1], f = cli[, 'group'])
simulation_Ic(2, samplesL, counts, B =3, fun="BioTIP", shrink=TRUE)

xyang2uchicago/NPS documentation built on June 30, 2024, 10:15 p.m.