naiveGramm: Corrlation methods of Gramm

In chentianlu/gramm4R: Generalized correlation analysis and model construction strategy for metabolome and microbiome

Description

A function to test the association among metabolites and microbes. Using linear (linear regression) or nonlinear (Maximal Information Coefficient) methods.

Usage

naiveGramm(x,y,z,r,alpha)

Arguments

x	A SummarizedExperiment object contains data of preproccessed data, where rows represent features of metabolites and columns represent samples.
y	A SummarizedExperiment object contains data of microbiome preproccessed data , where rows represent features of microbes and columns represent samples.
z	An optional SummarizedExperiment object containing the confounders.
r	The linear regression coefficients threshold for using nonlinear method. Default: 0.5.
alpha	The linear regression p-value threshold for using nonlinear method.Default: 0.05.

Value

r	Correlation coefficients.
p	Correlation p values.
type	Correlation methods for computing (linear or nonlinear).

Author(s)

Mengci Li, Dandan Liang, Tianlu Chen and Wei Jia

References

Chambers, J. M. (1992) Linear models. Chapter 4 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole. D. Reshef, Y. Reshef, H. Finucane, S. Grossman, G. McVean, P. Turnbaugh, E. Lander, M. Mitzenmacher, P. Sabeti. (2011) Detecting novel associations in large datasets. Science 334, 6062. D. Albanese, M. Filosi, R. Visintainer, S. Riccadonna, G. Jurman, C. Furlanello. minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers. Bioinformatics (2013) 29(3): 407-408.

See Also

preGramm for pretreatment;nlfitGramm for nonlinear fitting;Gramm: the whole strategy of this method.

Examples

data("metabolites")
data("microbes")
data("covariates")
naiveGramm(metabolites,microbes,covariates)

chentianlu/gramm4R documentation built on July 6, 2021, 2:43 p.m.