ceRNA.cor: identifying miRNA sponge interactions using ceRNA.cor...

In CeRNASeek: Identification and Analysis of ceRNA Regulation

Description

identifying miRNA sponge interactions using ceRNA.cor.In this function We implement several popular linear methods ( HyperC, SC) to identify miRNA sponge. interactions.

Usage

ceRNA.cor(miRtar, targetce = NULL, geneexp, miRexp, numMIR = 1, method = "pearson", 
numrandom = 100)

Arguments

miRtar	A data frame representing the relationship between miRNA and target. The data frame contains the name of the miRNA and target regulatory relationship.Required option for method "pearson" and "partial correlation".
targetce	a character string (vector) specifying candidate target name to analyse (default (targetce = NULL)).
geneexp	An input target expression data frame, the columns are genes and the rows are samples.The expression value may be gene expression ,non-coding RNA expression or expression values of circRNAs and so on. Required option for method pearson" and "partial correlation".
miRexp	An input miRNA expression data frame, the columns are miRNA and the rows are samples. Required option for method pearson" and "partial correlation".
numMIR	a numeric vector that specify the minimum number of 2 gene-shared miRNAs.
method	a character string (default "pearson") indicating which statistical method to choose to calculate the ceRNA interaction relationship. One of "pearson" (default), or "partial correlation", can be abbreviated.
numrandom	The number of random. Required option for method "partial correlation",default (numrandom = 100).

Details

Note:All the arguments without default value must be assigned.

Value

A list of identified miRNA sponge interactions containing following components:

• ceRNA predicted triplets and related information,a 5 columns dataframe as following:

  • targetce represented target names,respectively.

  • anotherce names of modulators that another target(modulators) constitutes a ceRNA interaction relation.

  • miRNAs names of miRNA shared by two targets.

  • miRNAs_num number of miRNAs shared by two targets.

  • correlation The correlation of the identified ceRNA interaction relation.

  • pvalue The p value of the identified ceRNA interaction relation.

• miR_l Number of miRNAs interacting with each target in the input file.

References

Paci P , Colombo T , Farina L . Computational analysis identifies a sponge interaction network between long non-coding RNAs and messenger RNAs in human breast cancer[J]. BMC Systems Biology, 2014, 8(1):83. Zhang Y , Xu Y , Feng L , et al. Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers[J]. Oncotarget, 2014, 7(39):64148-64167.

Examples

##identifying miRNA sponge interactions
##Here we take the regulatory relationship between six genes and 71 miRNAs  and corresponding
##expression profilesas an example.
ceRNA.cor(miRtar=dataset[["miRtar"]], targetce = NULL, geneexp=dataset[["geneexp"]],
          miRexp=dataset[["miRexp"]], numMIR = 1,method = "pearson", numrandom = 100)

CeRNASeek documentation built on April 29, 2020, 9:37 a.m.