convert_se_gene_ids {celaref} | R Documentation

## convert_se_gene_ids

### Description

Change the gene IDs in in the supplied datatset_se object to some other id already present in the gene info (as seen with `rowData()`)

### Usage

    convert_se_gene_ids(dataset_se, new_id, eval_col, find_max = TRUE)

### Arguments

`dataset_se` | Summarised experiment object containing count data. Also requires 'ID' and 'group' to be set within the cell information (see `colData()`)
`new_id` | A column within the feature information (view `colData(dataset_se)`)) of the dataset_se, which will become the new ID column. Non-uniqueness of this column is handled gracefully! Any NAs will be dropped.
`eval_col` | Which column to use to break ties of duplicate new_id. Must be a column within the feature information (view `colData(dataset_se)`)) of the dataset_se. Total reads per gene feature is a good choice.
`find_max` | If false, this will choose the minimal eval_col instead of max. Default = TRUE

### Value

A modified dataset_se - ID will now be new_id, and unique. It will have fewer genes if old ID to new ID was not a 1:1 mapping. The selected genes will be according to the eval col max (or min). should pick the alphabetical first on ties, but could change.

### See Also

SummarizedExperiment For general doco on the SummarizedExperiment objects.

`load_se_from_files` For reading data from flat files (not 10X cellRanger output)

### Examples

    # The demo dataset doesn't have other names, so make some up
    # (don't do this)
    dataset_se <- demo_ref_se
    rowData(dataset_se)$dummyname <- toupper(rowData(dataset_se)$ID)

    # If not already present, define a column to evaluate,
    # typically total reads/gene.
    rowData(dataset_se)$total_count <- rowSums(assay(dataset_se))

    dataset_se <- convert_se_gene_ids(dataset_se, new_id='dummyname', eval_col='total_count')

[Package celaref version 1.6.0 Index]