getIc: Get Index for Critical transition (Ic score)

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

Get Index for Critical transition (Ic score)

Description

Retrieve Ic scores (Pearson correlation of genes / Pearson correlation of samples) for the identified critical transition state

Usage

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

Arguments

counts	A numeric matrix or data frame. The rows and columns represent unique transcript IDs (geneID) and sample names, respectively.
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'.
genes	A character vector consisting of unique CTS gene ids. This can be obtained from getMaxMCImember
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)
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".

Value

A list of numeric values, whose length and names are inherited from sampleL

Author(s)

Zhezhen Wang [e-mail]; Xinan H Yang [e-mail]

References

Schafer and Strimmer (2005) "A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics"

M. Mojtahedi et al., Cell Fate Decision as High-Dimensional Critical State Transition. PLoS Biol 14, e2000640 (2016).

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'])
CTS = c('loci1', 'loci2')

## Comparing the results with an estiamted correlation matrix with that without estimation.
Ic = getIc(counts,  samplesL,  CTS, fun='cor')
Ic.2 = getIc(counts,  samplesL,  CTS, fun='BioTIP', shrink=FALSE)
BioTIP = getIc(counts,  samplesL,  CTS, fun='BioTIP')

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