anova2de: Use ANOVA to filter low epxressed genes

In wyguo/RLowPCor: Inference of co-expression gene network using relevance low order partial correlation from large scale expression data

Description

Analysis of variance is used to filter the low expressed genes. More details can be seen in aov.

Usage

anova2de(data.exp, ncol.idx, pval.cut = 0.05, model = "expression~time")

Arguments

data.exp	gene expression data matrix with variables in columns and samples in rows. The first columns are the indeces for comparison, such as time points and conditions for comparision.
ncol.idx	the number of index columns.
pval.cut	a numeric value for significance cut-off. The default is pval.cut=0.05.
model	the model used for comparison. The default is model="expression~time".

Value

anova2de returns a list includes the ANOVA p-value results, the names of differentially expressed genes and the time-series data of differential expressed genes.

See Also

aov, RLowPC

wyguo/RLowPCor documentation built on May 4, 2019, 12:04 p.m.