deconvolve_cellularity {tidybulk} | R Documentation

## Get cell type proportions from samples

### Description

deconvolve_cellularity() takes as input a 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> | and returns a 'tbl' with the estimated cell type abundance for each sample

### Usage

    deconvolve_cellularity(
      .data,
      .sample = NULL,
      .transcript = NULL,
      .abundance = NULL,
      reference = NULL,
      method = "cibersort",
      prefix = "",
      action = "add",
      ...
    )

    ## S4 method for signature 'spec_tbl_df'
    deconvolve_cellularity(
      .data,
      .sample = NULL,
      .transcript = NULL,
      .abundance = NULL,
      reference = NULL,
      method = "cibersort",
      prefix = "",
      action = "add",
      ...
    )

    ## S4 method for signature 'tbl_df'
    deconvolve_cellularity(
      .data,
      .sample = NULL,
      .transcript = NULL,
      .abundance = NULL,
      reference = NULL,
      method = "cibersort",
      prefix = "",
      action = "add",
      ...
    )

    ## S4 method for signature 'tidybulk'
    deconvolve_cellularity(
      .data,
      .sample = NULL,
      .transcript = NULL,
      .abundance = NULL,
      reference = NULL,
      method = "cibersort",
      prefix = "",
      action = "add",
      ...
    )

    ## S4 method for signature 'SummarizedExperiment'
    deconvolve_cellularity(
      .data,
      .sample = NULL,
      .transcript = NULL,
      .abundance = NULL,
      reference = NULL,
      method = "cibersort",
      prefix = "",
      action = "add",
      ...
    )

    ## S4 method for signature 'RangedSummarizedExperiment'
    deconvolve_cellularity(
      .data,
      .sample = NULL,
      .transcript = NULL,
      .abundance = NULL,
      reference = NULL,
      method = "cibersort",
      prefix = "",
      action = "add",
      ...
    )

### Arguments

`.data` | A 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> |
`.sample` | The name of the sample column
`.transcript` | The name of the transcript/gene column
`.abundance` | The name of the transcript/gene abundance column
`reference` | A data frame. The transcript/cell_type data frame of integer transcript abundance. If NULL, the default reference will be used for each algorithm. For llsr will be LM22.
`method` | A character string. The method to be used. At the moment Cibersort (default), epic and llsr (linear least squares regression) are available.
`prefix` | A character string. The prefix you would like to add to the result columns. It is useful if you want to reshape 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 Cibersort

### Details

'r lifecycle::badge("maturing")'

This function infers the cell type composition of our samples (with the algorithm Cibersort; Newman et al., 10.1038/nmeth.3337).

Underlying method: CIBERSORT(Y = data, X = reference, ...)

### Value

A 'tbl' object including additional columns for each cell type estimated

A 'tbl' object including additional columns for each cell type estimated

A 'tbl' object including additional columns for each cell type estimated

A 'tbl' object including additional columns for each cell type estimated

A 'SummarizedExperiment' object

A 'SummarizedExperiment' object

### Examples

    library(dplyr)

    # Subsetting for time efficiency
    tidybulk::se_mini %>% tidybulk() %>% filter(sample=="SRR1740034") %>% deconvolve_cellularity(sample, feature, count, cores = 1)

[Package tidybulk version 1.4.0 Index]