collapseTranscripts {ballgown} | R Documentation

## cluster a gene's transcripts and calculate cluster-level expression

### Description

cluster a gene's transcripts and calculate cluster-level expression

### Usage

    collapseTranscripts(gene, gown, meas = "FPKM", method = c("hclust",
      "kmeans"), k = NULL)

### Arguments

`gene` | which gene's transcripts should be clustered
`gown` | ballgown object
`meas` | which transcript-level expression measurement to use (`'cov'`, average per-base coverage, or `'FPKM'`)
`method` | which clustering method to use: `'hclust'` (hierarchical clustering) or `'kmeans'` (k-means clustering).
`k` | how many clusters to use.

### Value

list with two elements:

- `tab`, a cluster-by-sample table of expression measurements (`meas`, either cov or FPKM), where the expression measurement for each cluster is the mean (for `'cov'`) or aggregate (for `'FPKM'`, as in `gexpr`) expression measurement for all the transcripts in that cluster. This table can be used as the `gowntable` argument to `stattest`, if differential expression results for transcript *clusters* are desired.

- `cl` output from `clusterTranscripts` that was run to produce `tab`, for reference. Cluster IDs in the `cluster` component correspond to row names of `tab`

### Author(s)

Alyssa Frazee

### See Also

`hclust`, `kmeans`, `clusterTranscripts`, `plotLatentTranscripts`

### Examples

    data(bg)
    collapseTranscripts(bg, gene='XLOC_000454', meas='FPKM', method='kmeans')

[Package ballgown version 2.19.3 Index]