Source code from https://github.com/FFinotello/quanTIseq
deconvolute_quantiseq.default(mix.mat, arrays = FALSE, signame = "TIL10",
tumor = FALSE, mRNAscale = TRUE, method = "lsei", btotalcells = FALSE,
rmgenes = "unassigned")table with the gene TPM (or microarray expression values) for all samples to be deconvoluted (Gene symbols on the first column and sample IDs on the first row). Expression data must be on non-log scale
specifies whether expression data are from microarrays (instead of RNA-seq). If TRUE, the "--rmgenes" parameter is set to "none".
name of the signature matrix. Currently only TIL10 is available.
specifies whether expression data are from tumor samples. If TRUE, signature genes with high expression in tumor samples are removed (see 1). Default: FALSE.
specifies whether cell fractions must be scaled to account for cell-type-specific mRNA content. Default: TRUE.
deconvolution method to be used: "hampel", "huber", or "bisquare" for robust regression with Huber, Hampel, or Tukey bisquare estimators, respectively, or "lsei" for constrained least squares regression. The fraction of uncharacterized cells ("other") is computed only by the "lsei" method. Default: "lsei".
compute cell densities instead of fractions Default: FALSE
Default: "default" for RNAseq, "none" for microArray data
F. Finotello, C. Mayer, C. Plattner, G. Laschober, D. Rieder, H. Hackl, A. Krogsdam, W. Posch, D. Wilflingseder, S. Sopper, M. Jsselsteijn, D. Johnsons, Y. Xu, Y. Wang, M. E. Sanders, M. V. Estrada, P. Ericsson-Gonzalez, J. Balko, N. F. de Miranda, Z. Trajanoski. "quanTIseq: quantifying immune contexture of human tumors". bioRxiv 223180. https://doi.org/10.1101/223180.