merge-methods {mia} | R Documentation

## Merge a subset of the rows or columns of a `SummarizedExperiment`

### Description

`mergeRows`/`mergeCols` merge data on rows or columns of a `SummarizedExperiment` as defined by a `factor` alongside the chosen dimension. Metadata from the `rowData` or `colData` are retained as defined by `archetype`.

### Usage

    mergeRows(x, f, archetype = 1L, ...)

    mergeCols(x, f, archetype = 1L, ...)

    ## S4 method for signature 'SummarizedExperiment'
    mergeRows(x, f, archetype = 1L, ...)

    ## S4 method for signature 'SummarizedExperiment'
    mergeCols(x, f, archetype = 1L, ...)

    ## S4 method for signature 'TreeSummarizedExperiment'
    mergeRows(x, f, archetype = 1L, mergeTree = FALSE, mergeRefSeq = FALSE, ...)

    ## S4 method for signature 'TreeSummarizedExperiment'
    mergeCols(x, f, archetype = 1L, mergeTree = FALSE, ...)

### Arguments

`x` | a `SummarizedExperiment` or a `TreeSummarizedExperiment`
`f` | A factor for merging. Must be the same length as `nrow(x)/ncol(x)`. Rows/Cols corresponding to the same level will be merged. If `length(levels(f)) == nrow(x)/ncol(x)`, `x` will be returned unchanged.
`archetype` | Of each level of `f`, which element should be regarded as the archetype and metadata in the columns or rows kept, while merging? This can be single integer value or an integer vector of the same length as `levels(f)`. (Default: `archetype = 1L`, which means the first element encountered per factor level will be kept)
`...` | optional arguments: passed onto `sumCountsAcrossFeatures`, except `subset_row`, `subset_col`
`mergeTree` | `TRUE` or `FALSE`: should to `rowTree()` also be merged? (Default: `mergeTree = FALSE`)
`mergeRefSeq` | `TRUE` or `FALSE`: should a consensus sequence calculate? If set to `FALSE`, the result from `archetype` is returned; If set to `TRUE` the result from `DECIPHER::ConsensusSequence` is returned. (Default: `mergeRefSeq = FALSE`)

### Details

`assay` are agglomerated, i.e.. summed up. Other than counts / absolute values might lead to meaningless values.

These functions are similar to `sumCountsAcrossFeatures`. However, additional support for `TreeSummarizedExperiment` was added and science field agnostic names were used. In addition the `archetype` argument lets the user select how to preserve row or column data.

For merge data of assays the function from `scuttle` are used.

### Value

an object with the same class `x` with the specified entries merged into one entry in all relevant components.

### See Also

`sumCountsAcrossFeatures`

### Examples

    data(esophagus)
    esophagus
    plot(rowTree(esophagus))
    # get a factor for merging
    f <- factor(regmatches(rownames(esophagus),
                           regexpr("^[0-9]*_[0-9]*",rownames(esophagus))))
    merged <- mergeRows(esophagus,f)
    plot(rowTree(merged))
    #
    data(GlobalPatterns)
    GlobalPatterns
    merged <- mergeCols(GlobalPatterns,colData(GlobalPatterns)$SampleType)
    merged

[Package mia version 1.2.7 Index]