segmentation {segmenter} | R Documentation

## segmentation objects

### Description

The `segmentation` class consists of matrices and lists. The components contain the output of the chromatin segmentation analysis. Loading the input data is optional. The object is returned as a result of calling `learn_model` or reading its already existing output.

### Slots

`model`

  list. The `list` consists of 6 items corresponding to the contents of the `model_#.txt` file. These are `number_states` and `number_marks` for the numbers of states and marks in the model; `likelihood` and `probinit` for the likelihood and the initial probabilities of the multi-state model; `transitionprobs` and `emissionprobs` for the probabilities of the transitions and emissions parameters of the model. Can be accessed using `model`.

`emission`

  matrix. The `matrix` contains the emission parameters of n states (rows) for n marks (columns) corresponding to the contents of the `emission_#.txt` file. Can be accessed using `emission`.

`transition`

  matrix. The `matrix` contains the transition parameters of n by n states corresponding to the contents of the `transition_#.txt` file. Can be accessed using `transition`.

`overlap`

  list. A `list` of n number of cells/conditions items. Each item is a `matrix` of the overlap enrichment of n states (rows) at n genomic annotations (columns) corresponding to the contents of the `<cell>_#_overlap.txt` files. Can be accessed using `overlap`.

`TSS`

  list. A `list` of n number of cells/conditions items. Each item is a `matrix` of the overlap enrichment of n states (rows) at n locations around the transcription start site (TSS) (columns) corresponding to the contents of the `<cell>_#_TSS_neighborhood.txt` files. Can be accessed using `TSS`.

`TES`

  list. A `list` of n number of cells/conditions items. Each item is a `matrix` of the overlap enrichment of n states (rows) at n locations around the transcription end site (TES) (columns) corresponding to the contents of the `<cell>_#_TES_neighborhood.txt` files. Can be accessed using `TES`.

`segment`

  list. A `list` of n number of cells/conditions items. Each item is a `GRanges` object containing the segmentation and assigned states as a metadata column 'state'. These contents correspond to the `<cell>_#_segment.bed` files. Annotations of the ranges are optional. Can be accessed using `segment`.

`bins`

  list. A `list` of n number of cells/conditions items. Each item is a `SummarizedExperiment` object containing the binarized input data. The coordinates of the bins are saved as the `rowRanges` each assigned to a state and the binary data itself is saved as `assay`. Can be accessed using `bins`.

`counts`

  list. A `list` of n number of cells/conditions items. Each item is a `SummarizedExperiment` object containing the read counts in bins. The coordinates of the bins are saved as the `rowRanges` each assigned to a state and the counts data itself is saved as `assay`. Can be accessed using `counts`.

### See Also

`learn_model`

[Package segmenter version 1.0.0 Index]