cluster_elements {tidybulk} | R Documentation

## Get clusters of elements (e.g., samples or transcripts)

### Description

cluster_elements() takes as imput a 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> | and identify clusters in the data.

### Usage

    cluster_elements(
      .data,
      .element = NULL,
      .feature = NULL,
      .abundance = NULL,
      method,
      of_samples = TRUE,
      log_transform = TRUE,
      action = "add",
      ...
    )

### Arguments

`.data` | A 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> |
`.element` | The name of the element column (normally samples).
`.feature` | The name of the feature column (normally transcripts/genes)
`.abundance` | The name of the column including the numerical value the clustering is based on (normally transcript abundance)
`method` | A character string. The cluster algorithm to use, ay the moment k-means is the only algorithm included.
`of_samples` | A boolean. In case the input is a tidybulk object, it indicates Whether the element column will be sample or transcript column
`log_transform` | A boolean, whether the value should be log-transformed (e.g., TRUE for RNA sequencing data)
`action` | A character string. Whether to join the new information to the input tbl (add), or just get the non-redundant tbl with the new information (get).
`...` | Further parameters passed to the function kmeans

### Details

identifies clusters in the data, normally of samples. This function returns a tibble with additional columns for the cluster annotation. At the moment only k-means clustering is supported, the plan is to introduce more clustering methods.

### Value

A tbl object with additional columns with cluster labels

### Examples

        cluster_elements(tidybulk::counts_mini, sample, transcript, count,	centers = 2, method="kmeans")

[Package tidybulk version 0.99.23 Index]