AnnotateResults {rnaEditr} | R Documentation

## Add Annotations to site-specific or region-based analysis results.

### Description

Add annotations to site-specific or region-based analysis results from function `TestAssociations`.

### Usage

    AnnotateResults(
      results_df,
      closeByRegions_gr = NULL,
      inputRegions_gr = NULL,
      genome = c("hg38", "hg19"),
      analysis = c("region-based", "site-specific")
    )

### Arguments

`results_df` | An output data frame from function `TestAssociations`, which includes variables for locations and result of statistical tests for the genomic sites or regions.
`closeByRegions_gr` | An output GRanges object from function `AllCloseByRegions`, defaults to `NULL`.
`inputRegions_gr` | A GRanges object for input genomic regions, defaults to `NULL`.
`genome` | Use `"hg19"` or `"hg38"` gene reference. Defaults to `"hg38"`.
`analysis` | Results type. Defaults to `"region-based"`. When it's set to `"site-specific"`, arguments `closeByRegions_gr` and `inputRegions_gr` will not be used and set to NULL automatically.

### Value

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

### See Also

`TransformToGR`, `AllCloseByRegions`, `AllCoeditedRegions`, `CreateEditingTable`, `SummarizeAllRegions`, `TestAssociations`

### Examples

      data(rnaedit_df)

      # get GRanges for genes
      genes_gr <- TransformToGR(
        genes_char = c("PHACTR4", "CCR5", "METTL7A"),
        type = "symbol",
        genome = "hg19"
      )

      # find close-by regions within the genes
      closebyRegions_gr <- AllCloseByRegions(
        regions_gr = genes_gr,
        rnaEditMatrix = rnaedit_df
      )

      # identify co-edited regions within the genes
      coedited_gr <- AllCoeditedRegions(
        regions_gr = closebyRegions_gr,
        rnaEditMatrix = rnaedit_df,
        output = "GRanges",
        method = "spearman"
      )

      # summarize editing levels within each gene by maximum
      summarizedRegions_df <- SummarizeAllRegions(
        regions_gr = coedited_gr,
        rnaEditMatrix = rnaedit_df,
        selectMethod = MaxSites
      )

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

      # test summarized editing levels against survival outcome
      results_df <- TestAssociations(
        rnaEdit_df = summarizedRegions_df,
        pheno_df = exm_pheno,
        responses_char = "sample_type",
        covariates_char = NULL,
        respType = "binary"
      )

      AnnotateResults(
        results_df = results_df,
        closeByRegions_gr = closebyRegions_gr,
        inputRegions_gr = genes_gr,
        genome = "hg19"
      )

[Package rnaEditr version 1.2.0 Index]