aggregateFeatures {scDblFinder} | R Documentation

## aggregateFeatures

### Description

Aggregates similar features (rows).

### Usage

    aggregateFeatures(
      x,
      dims.use = seq(2L, 12L),
      k = 1000,
      num_init = 2,
      use.mbk = NULL,
      use.subset = 5000,
      use.TFIDF = TRUE,
      ...
    )

### Arguments

`x` | A integer/numeric (sparse) matrix, or a 'SingleCellExperiment' including a 'counts' assay.
`dims.use` | The PCA dimensions to use for clustering rows.
`k` | The approximate number of meta-features desired
`num_init` | The number of initializations used for k-means clustering.
`use.mbk` | Logical; whether to use minibatch k-means (see `mbkmeans`). If NULL, the minibatch approach will be used if there are more than 30000 features.
`use.subset` | How many cells (columns) to use to cluster the features.
`use.TFIDF` | Logical; whether to use TFIDF normalization (instead of standard normalization) to assess the similarity between features. similarity
`...` | Passed to `mbkmeans`. Can for instance be used to pass the 'BPPARAM' argument for multithreading.

### Value

An aggregated version of 'x' (either an array or a 'SingleCellExperiment', depending on the input).

[Package scDblFinder version 1.8.0 Index]