TestAssociations {rnaEditr} | R Documentation

## Test associations between phenotype and RNA editing levels.

### Description

A wrapper function to test associations between phenotype and RNA editing levels in single-site analysis or summarized RNA editing levels in region-based analysis.

### Usage

    TestAssociations(
      rnaEdit_df,
      pheno_df,
      responses_char,
      covariates_char = NULL,
      respType = c("binary", "continuous", "survival"),
      progressBar = "time",
      orderByPval = TRUE
    )

### Arguments

`rnaEdit_df` | A data frame with class `rnaEdit_df`, which is a output from function `CreateEditingTable()` or function `SummarizeAllRegions()`. This data frame should include RNA editing level values, with row names as site IDs or region IDs, and column names as sample IDs.
`pheno_df` | A data frame with phenotype and covariates, which should include all the samples in `rnaEdit_df`. Please make sure the input `pheno_df` has the variable named `"sample"` to indicate sample IDs.
`responses_char` | A character vector of names of response variables in `pheno_df`. When respType is set as `"survival"`, `responses_char` should have length 2. The first element must be the name of the variable with following up time, and the second element must be status indicator. Status indicator should be coded as 0/1(1=death), TRUE/FALSE(TRUE=death), or 1/2(death). Please make sure variable names are in this order. We have not tested this code on interval-censored data; use at your own risk. See `Surv` for more details.
`covariates_char` | A character vector of names of covariate variables in `pheno_df`.
`respType` | Type of outcome. Defaults to `"binary"`.
`progressBar` | Name of the progress bar to use. There are currently five types of progress bars: `"time"`, `"none"`, `"text"`, `"tk"`, and `"win"`. Defaults to `"time"`. See `create_progress_bar` for more details.
`orderByPval` | Sort co-edited regions by model p-value or not? Defaults to TRUE.

### Value

A data frame with locations of the genomic regions or sites (`seqnames, start, end, width`), test statistics (`estimate, stdErr` or `coef, exp_coef, se_coef`), `pValue` and false discovery rate (`fdr`).

### See Also

`TransformToGR`, `AllCloseByRegions`, `AllCoeditedRegions`, `CreateEditingTable`, `SummarizeAllRegions`, `AnnotateResults`

### Examples

      data(rnaedit_df)

      genes_gr <- TransformToGR(
        genes_char = c("PHACTR4", "CCR5", "METTL7A"),
        type = "symbol",
        genome = "hg19"
      )

      exm_regions <- AllCoeditedRegions(
        regions_gr = genes_gr,
        rnaEditMatrix = rnaedit_df,
        output = "GRanges",
        method = "spearman"
      )

      sum_regions <- SummarizeAllRegions(
        regions_gr = exm_regions,
        rnaEditMatrix = rnaedit_df,
        selectMethod = MaxSites
      )

      exm_pheno <- readRDS(
        system.file(
        "extdata",
        "pheno_df.RDS",
        package = 'rnaEditr',
        mustWork = TRUE
        )
      )

      TestAssociations(
        rnaEdit_df = sum_regions,
        pheno_df = exm_pheno,
        responses_char = "sample_type",
        covariates_char = NULL,
        respType = "binary"
      )

[Package rnaEditr version 1.4.0 Index]