POSTglm: POST of Generalized Linear Model

In POST: Projection onto Orthogonal Space Testing for High Dimensional Data

Description

Peform POST analysis with linear model

Usage

POSTglm (exprSet, geneSet, lamda = 0.95, seed = 13, nboots = 100, 
    model = "Group ~ ", family = binomial(link = "logit"), ...) 

Arguments

exprSet	an ExpressionSet class contains minimum of exprs (expression matrix) of genomic data such as gene expression and phenoData (AnnotatedDataFrame of end point data). Please refer to Biobase for details on how to create such an ExpressionSet expression set.
geneSet	a GeneSetCollection class with minimum of setName and geneIDs for each GeneSet. Please refer to GSEABase for how to create such a GeneSetCollection class.
lamda	a predefined fraction of 0 to 1: the fraction of variation retained in the selected orthogonal projections
seed	seed of random number generator
nboots	number of bootstrap samples, default=100
model	a character string to define the model
family	a description of the error distribution and link function to be used in the model. For glm, this can be a character string naming a family function, a family function or the result of a call to a family function.
...	control arguments to be passed to generalized linear model, default control argument are used if they are not supplied directly

Details

The function performs POST analysis for association of gene sets with phenotype in generalized linear model framework.

Value

a data frame with 5 columns

GeneSet	Gene set id
Nprobe	numbe of probes in the ExpressionSet annotated to the gene set
Nproj	number of projected vectors included in the POST analysis
Stat	statistic of quadratic form
p.value	p value of generalized Chi-square approximation

Author(s)

Xueyuan Cao [e-mail], Stanley Pounds [e-mail]

Examples

 ## load data
  data(sampExprSet)
  data(sampGeneSet)
 test<-POSTglm(exprSet=sampExprSet,                         
               geneSet=sampGeneSet,                         
               lamda=0.95,                      
               seed=13,                        
               nboots=100,                      
               model='Group ~ ',   
               family=binomial(link = "logit")) 
 

POST documentation built on Nov. 8, 2020, 6:49 p.m.