Creating The Example Data Set
In RNAseqQC: Quality Control for RNA-Seq Data

Here we quickly show how the data objects of the example data set can be reproduced.

Load Packages

library("recount3")
library("DESeq2")
library("dplyr")
library("stringr")
library("SummarizedExperiment")
library("tidyr")
library("tibble")
library("magrittr")

Download GSE89888 via recount3 and format data

# download data recount3
proj_info <- available_projects() %>%
  filter(project == "SRP093386")
se <- create_rse(proj_info)

count_mat <- compute_read_counts(se)
rownames(count_mat) <- str_replace(rownames(count_mat), "\\.[:number:]+$", "")

meta <- colData(se) %>%
  as_tibble() %>%
  separate(sra.sample_title, into = c("cell_line", "treatment", "mutation", "replicate"), sep = "-") %>%
  select(cell_line, treatment, mutation, replicate)

colnames(count_mat) <- paste0(meta$treatment, "_", meta$mutation, "_", meta$replicate)

# subset to cell line T47D
count_mat <- count_mat[, meta$cell_line == "T47D"]
meta <- meta[meta$cell_line == "T47D", c("treatment", "mutation", "replicate")]

T47D <- make_dds(count_mat, meta, ah_record = "AH89426")
T47D <- T47D[rowSums(assay(T47D))>0,]

# round some numeric data to reduce the size of the data object
rowData(T47D)$gc_content <- round(rowData(T47D)$gc_content,1)

Differential testing

dds <- T47D
dds <- filter_genes(dds, min_count = 5, min_rep = 4)
dds$mutation <- as.factor(dds$mutation)
dds$treatment <- as.factor(dds$treatment)
design(dds) <- ~ mutation + treatment

# to not run DESeq2 in the main vignette,
# wo pre-compute the dispersion plot and diff testing results
dds <- DESeq(dds, parallel=T)

png(filename="disp_ests.png", width=7, height=5, units="in", res=200)
plotDispEsts(dds)
dev.off()

T47D_diff_testing <- lfcShrink(dds, coef = "mutation_WT_vs_D538G", lfcThreshold = log2(1.5), type = "normal", parallel = TRUE)
T47D_diff_testing$stat <- NULL
T47D_diff_testing$lfcSE <- NULL
T47D_diff_testing$pvalue <- NULL