Perform DE of multiple samples in a screen vs control

Usage

compute_multi_de(
  data = NULL,
  treatment_samples = NULL,
  control_samples = NULL,
  method = "edgeR",
  num_cores = 2,
  batch = 1,
  k = 2,
  spikes = NULL
)

Arguments

data: A tidyseurat object merged with metadata. Must contain columns "Well_ID", "Row", "Column"
treatment_samples: Value in the column "combined_id" representing replicates of treatment samples in the data
control_samples: Value in the column "combined_id" representing replicates of control samples in the data
method: One of "Seurat_wilcox", "DESeq2", "edgeR", "RUVg", "RUVs", "RUVr", "limma_voom"
num_cores: Number of cores
batch: Either empty, a single value, or a vector corresponding to the number of samples
k: Parameter k for RUVSeq methods, check RUVSeq tutorial
spikes: List of genes to use as spike controls

Value

List of DE counts vs control

Examples

data("mini_mac")
control_samples <- "DMSO_0"
mini_mac$combined_id<-make.names(mini_mac$combined_id)
treatment_samples <- c("Staurosporine_10", "Paclitaxel_10", 
"Chlorambucil_10", "Vinblastine_sulfate_10", "Etoposide_10" , 
"Cytarabine_10", "Camptothecin_10", "Anastrozole_10", 
"Sb590885_10", "Fluvastatin_sodium_10")
mini_mac_test<-compute_multi_de(mini_mac, treatment_samples, 
control_samples, num_cores = 1, method = "edgeR")