negative_cor: Find the correlation coefficient between each gene and miRNA.

In anamiR: An integrated analysis package of miRNA and mRNA expression data

Description

This function will calculate the correlation coefficient between each gene and miRNA from differential expressed data, which are produced by differExp_discrete or differExp_continuous. After filtering the positive and higher than cutoff value of correlation, this function would return a matrix with seven columns, including miRNA, gene, correlation coefficients and Fold change, P-adjust value for miRNA and gene. Each row represents one potential miRNA-target gene interaction.

Usage

negative_cor(mrna_data, mirna_data, method = c("pearson", "kendall",
  "spearman"), cut.off = -0.5)

Arguments

mrna_data	differential expressed data in matrix format, with sample name in columns and gene symbol in rows, which is generated by differExp_discrete or differExp_continuous.
mirna_data	differential expressed data in matrix format, with sample name in columns and miRNA in rows, which is generated by differExp_discrete or differExp_continuous, miRNA should be miRBase 21 version now.
method	methods for calculating correlation coefficient, including "pearson", "spearman", "kendall". Default is "pearson". From function cor
cut.off	an numeric value indicating a threshold of correlation coefficient for every potential miRNA-genes interactions. Default is -0.5, however, if no interaction pass the threshold, this function would add 0.2 value in threshold until at least one interaction passed the threshold.

Value

matrix format with each row indicating one potential miRNA-target gene interaction and seven columns are miRNA, gene, correlation coefficient and Fold change, P-adjust value for miRNA and gene.

See Also

cor for calculation of correlation.

Examples

## Use the internal dataset
data("mirna", package = "anamiR", envir = environment())
data("pheno.mirna", package = "anamiR", envir = environment())
data("mrna", package = "anamiR", envir = environment())
data("pheno.mrna", package = "anamiR", envir = environment())

## SummarizedExperiment class
require(SummarizedExperiment)
mirna_se <- SummarizedExperiment(
 assays = SimpleList(counts=mirna),
 colData = pheno.mirna)

## SummarizedExperiment class
require(SummarizedExperiment)
mrna_se <- SummarizedExperiment(
 assays = SimpleList(counts=mrna),
 colData = pheno.mrna)

## Finding differential miRNA from miRNA expression data with t.test
mirna_d <- differExp_discrete(
   se = mirna_se,
   class = "ER",
   method = "t.test"
)

## Finding differential mRNA from mRNA expression data with t.test
mrna_d <- differExp_discrete(
   se = mrna_se,
   class = "ER",
   method = "t.test"
)

## Correlation
cor <- negative_cor(mrna_data = mrna_d, mirna_data = mirna_d,
     method = "pearson"
)

anamiR documentation built on Oct. 31, 2019, 8:55 a.m.