database_support {anamiR} | R Documentation

## Intersect with databases for potential miRNA-target gene interactions

### Description

This function will interst potential miRNA-target gene interactions from the input matrix, which is generated by negative_cor or miR_converter, with 8 predict databases and 2 validate databases about miRNA-target gene interactions. If the input caontains hundreds of interactions, it would take a few minutes to intersect all of them.

### Usage

    database_support(cor_data, org = "hsa", Sum.cutoff = 2)

### Arguments

`cor_data` | matrix format generated from negative_cor or miR_converter, including miRNA, gene, correlation coefficient for column names.
`org` | species of genes and miRNAs, only support "hsa", "mmu"
`Sum.cutoff` | a Threshold for total hits by predict databases. This one should not be greater than 8. Default is 2.

### Value

data.frame format. Each row represent one potential interaction. The first four columns are information about interactions: miRNA, gene symbol, Ensembl ID, gene ID, as for column 5 to 12 represent the predict dataases, while column 13 to 14 are validate databases. if databases truly hit this interactions, the number in it would be 1. The column 'Sum' means total hits by 8 databases, and column 'Validate' would be TRUE if at least one validate database hit the interaction. Furthermore, 'Fold-Change' and 'P-adjust' can also be found in this output, and if the 'de novo' column contains 1 means that row is not supported by any databases. The column 'evidence' represents if the experiment for validation is strong or limited, considering http://mirtarbase.mbc.nctu.edu.tw/.

### 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"
    )

    ## Convert annotation to miRBse 21
    mirna_21 <- miR_converter(data = mirna_d, original_version = 17)

    ## Correlation
    cor <- negative_cor(mrna_data = mrna_d, mirna_data = mirna_21)

    ## Intersect with known databases
    sup <- database_support(cor_data = cor)

[Package anamiR version 1.8.0 Index]