calculateCorr: Calculates the correlation coefficient values between two...

In guldenolgun/NoRCE: NoRCE: Noncoding RNA Sets Cis Annotation and Enrichment

Calculates the correlation coefficient values between two custom expression data.

Description

Calculates the correlation coefficient values between two custom expression data.

Usage

calculateCorr(
  exp1,
  exp2,
  label1 = "",
  label2 = "",
  corrMethod = "pearson",
  varCutoff = 0.0025,
  corCutoff = 0.3,
  pcut = 0.05,
  alternate = "greater",
  conf = 0.95
)

Arguments

exp1	Custom expression data matrix or SummarizedExperiment data. Columns must be genes and rows must be patients.
exp2	Custom expression data matrix or SummarizedExperiment data. Columns must be genes and rows must be patients.
label1	Gene names of the custom exp1 expression data. If it is not provided, column name of the exp1 data will be taken.
label2	Gene names of the custom exp2 expression data. If it is not provided, column name of the exp2 data will be taken.
corrMethod	Correlation coeffient method that will be used for evaluation. Possible values are "pearson", "kendall", "spearman"
varCutoff	Variance cut off that genes have less variance than this value will be trimmed
corCutoff	Correlation cut off values for the given correlation method
pcut	P-value cut off for the correlation values
alternate	Holds the alternative hypothesis and "two.sided", "greater" or "less" are the possible values.
conf	Confidence level for the returned confidence interval. It is only used for the Pearson correlation coefficient if there are at least 4 complete pairs of observations.

Value

Pairwise relations between gene-gene with corresponding correlation value and pvalue

Examples

## Not run: 
#Assume that mirnanorce and mrnanorce are custom patient by gene data
a<-calculateCorr(exp1 = mirna, exp2 = mrna ) 

## End(Not run)

guldenolgun/NoRCE documentation built on Oct. 21, 2022, 11:48 a.m.