auto_predict_grid {musicatk} | R Documentation

## Automatic filtering of signatures for exposure prediction gridded across specific annotation

### Description

Automatic filtering of signatures for exposure prediction gridded across specific annotation

### Usage

    auto_predict_grid(
      musica,
      table_name,
      signature_res,
      algorithm,
      sample_annotation = NULL,
      min_exists = 0.05,
      proportion_samples = 0.25,
      rare_exposure = 0.4,
      verbose = TRUE,
      combine_res = TRUE
    )

### Arguments

`musica` | Input samples to predit signature weights
`table_name` | Name of table used for posterior prediction (e.g. SBS96)
`signature_res` | Signatures to automatically subset from for prediction
`algorithm` | Algorithm to use for prediction. Choose from "lda_posterior", decompTumor2Sig, and deconstructSigs
`sample_annotation` | Annotation to grid across, if none given, prediction subsetting on all samples together
`min_exists` | Threshold to consider a signature active in a sample
`proportion_samples` | Threshold of samples to consider a signature active in the cohort
`rare_exposure` | A sample will be considered active in the cohort if at least one sample has more than this threshold proportion
`verbose` | Print current annotation value being predicted on
`combine_res` | Automatically combines a list of annotation results into a single result object with zero exposure values for signatures not found in a given annotation's set of samples

### Value

A list of results, one per unique annotation value, if no annotation value is given, returns a single result for all samples, or combines into a single result if combines_res = TRUE

### Examples

    data(musica_annot)
    data(cosmic_v2_sigs)
    auto_predict_grid(musica = musica_annot, table_name = "SBS96",
    signature_res = cosmic_v2_sigs, algorithm = "lda",
    sample_annotation = "Tumor_Subtypes")
    auto_predict_grid(musica_annot, "SBS96", cosmic_v2_sigs, "lda")

[Package musicatk version 1.0.0 Index]