cluster_elements-methods: Get clusters of elements (e.g., samples or transcripts)

In tidybulk: Brings transcriptomics to the tidyverse

Description

cluster_elements() takes as input 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",
  ...
)

## S4 method for signature 'spec_tbl_df'
cluster_elements(
  .data,
  .element = NULL,
  .feature = NULL,
  .abundance = NULL,
  method,
  of_samples = TRUE,
  log_transform = TRUE,
  action = "add",
  ...
)

## S4 method for signature 'tbl_df'
cluster_elements(
  .data,
  .element = NULL,
  .feature = NULL,
  .abundance = NULL,
  method,
  of_samples = TRUE,
  log_transform = TRUE,
  action = "add",
  ...
)

## S4 method for signature 'tidybulk'
cluster_elements(
  .data,
  .element = NULL,
  .feature = NULL,
  .abundance = NULL,
  method,
  of_samples = TRUE,
  log_transform = TRUE,
  action = "add",
  ...
)

## S4 method for signature 'SummarizedExperiment'
cluster_elements(
  .data,
  .element = NULL,
  .feature = NULL,
  .abundance = NULL,
  method,
  of_samples = TRUE,
  log_transform = TRUE,
  action = "add",
  ...
)

## S4 method for signature 'RangedSummarizedExperiment'
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, at 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

\lifecycle

maturing

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 (DOI: 10.2307/2346830) and SNN clustering (DOI:10.1016/j.cell.2019.05.031) is supported, the plan is to introduce more clustering methods.

Underlying method for kmeans do.call(kmeans(.data, iter.max = 1000, ...)

Underlying method for SNN .data Seurat::CreateSeuratObject() Seurat::ScaleData(display.progress = TRUE,num.cores = 4, do.par = TRUE) Seurat::FindVariableFeatures(selection.method = "vst") Seurat::RunPCA(npcs = 30) Seurat::FindNeighbors() Seurat::FindClusters(method = "igraph", ...)

Value

A tbl object with additional columns with cluster labels

A tbl object with additional columns with cluster labels

A tbl object with additional columns with cluster labels

A tbl object with additional columns with cluster labels

A 'SummarizedExperiment' object

A 'SummarizedExperiment' object

Examples

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

tidybulk documentation built on April 7, 2021, 6 p.m.