quanTIseq deconvolution for RNA-seq immune cell fractions.
Examples
eset_stad <- load_data("eset_stad")
anno_grch38 <- load_data("anno_grch38")
eset <- anno_eset(eset = eset_stad, annotation = anno_grch38, probe = "id")
#> ℹ Row number of original eset: 60483
#> ✔ 100% of probes in expression set were annotated
#> ℹ Found 2293 duplicate symbols, using "mean" method
#> ℹ Row number after filtering duplicated gene symbol: 50181
eset <- eset[1:500, 1:3]
res <- deconvo_quantiseq(
eset = eset, project = "stad", tumor = TRUE,
arrays = FALSE, scale_mrna = FALSE
)
#> ℹ Running quanTIseq deconvolution
#> ℹ Running quanTIseq deconvolution module
#> ℹ Gene expression normalization and re-annotation (arrays: FALSE)
#> ℹ Removing 17 noisy genes
#> ℹ Removing 15 genes with high expression in tumors
#> ℹ Signature genes found in data set: 0/138 (0%)
#> ℹ Mixture deconvolution (method: lsei)
#> ✔ Deconvolution successful!
head(res)
#> ID ProjectID B_cells_quantiseq Macrophages_M1_quantiseq
#> 1 TCGA-BR-6455 stad NaN NaN
#> 2 TCGA-BR-7196 stad NaN NaN
#> 3 TCGA-BR-8371 stad NaN NaN
#> Macrophages_M2_quantiseq Monocytes_quantiseq Neutrophils_quantiseq
#> 1 NaN NaN NaN
#> 2 NaN NaN NaN
#> 3 NaN NaN NaN
#> NK_cells_quantiseq T_cells_CD4_quantiseq T_cells_CD8_quantiseq
#> 1 NaN NaN NaN
#> 2 NaN NaN NaN
#> 3 NaN NaN NaN
#> Tregs_quantiseq Dendritic_cells_quantiseq Other_quantiseq
#> 1 NaN NaN NaN
#> 2 NaN NaN NaN
#> 3 NaN NaN NaN