quanTIseq {quantiseqr} | R Documentation

## Run quanTIseq deconvolution

### Description

Run quanTIseq deconvolution

### Usage

    quanTIseq(currsig, currmix, scaling = TRUE, method = "lsei")

### Arguments

`currsig` | Signature matrix to be used for deconvolution (format: genes by cell types).
`currmix` | Mixture matrix to be deconvoluted (format: genes by samples).
`scaling` | Logical value. If set to FALSE, it disables the correction of cell-type-specific mRNA content bias. Default: TRUE
`method` | Character string, defining the deconvolution method to be used: `lsei` for constrained least squares regression, `hampel`, `huber`, or `bisquare` for robust regression with Huber, Hampel, or Tukey bisquare estimators, respectively. Default: `lsei`.

### Value

A data.frame of cell fractions, cell types by samples.

### Examples

    data(dataset_racle)
    mixture <- dataset_racle$expr_mat
    signature.file <- system.file(
      "extdata", "TIL10_signature.txt", package = "quantiseqr", mustWork = TRUE)
    signature <- read.table(signature.file, header = TRUE, sep = "\t", row.names = 1)
    # cellfrac <- quantiseqr:::quanTIseq(mixture, signature)

[Package quantiseqr version 1.2.0 Index]