negative_cor {anamiR} | R Documentation

## Find the correlation coefficient between each gene and miRNA.

### 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"
    )

[Package anamiR version 1.8.0 Index]