CDF: Old version of CDF function

In ccdf: Distribution-Free Single-Cell Differential Expression Analysis

Description

Old version of CDF function

Usage

CDF(Y, X, Z = NULL, method = "linear regression", fast = TRUE)

Arguments

Y	a numeric vector of size n containing the preprocessed expressions from n samples (or cells).
X	a data frame containing numeric or factor vector(s) of size n containing the variable(s) to be tested (the condition(s) to be tested).
Z	a data frame containing numeric or factor vector(s) of size n containing the covariate(s).
method	a character string indicating which method to use to compute the CCDF, either 'linear regression', 'logistic regression' and 'permutations' or 'RF' for Random Forests. Default is 'linear regression' since it is the method used in the test.
fast	a logical flag indicating whether the fast implementation of logistic regression should be used. Only if 'dist_permutations' is specified. Default is TRUE.

Value

A list with the following elements:

• cdf: a vector of the cumulative distribution function of a given gene.

• ccdf: a vector of the conditional cumulative distribution function of a given gene, computed given X. Only if Z is NULL.

• ccdf_nox: a vector of the conditional cumulative distribution function of a given gene, computed given Z only (i.e. X is ignored.). Only if Z is not NULL.

• ccdf_x: a vector of the conditional cumulative distribution function of a given gene, computed given X and Z. Only if Z is not NULL.

• y_sort: a vector of the sorted expression points at which the CDF and the CCDFs are calculated.

• x_sort: a vector of the variables associated with y_sort.

• z_sort: a vector of the covariates associated with y_sort. Only if Z is not NULL.

Examples

X <- as.factor(rbinom(n=100, size = 1, prob = 0.5))
Y <- ((X==1)*rnorm(n = 50,0,1)) + ((X==0)*rnorm(n = 50,0.5,1))
res <- CDF(Y,X,method="linear regression")

ccdf documentation built on Sept. 24, 2021, 9:07 a.m.