# Differential expression analysis ----------------------------------------
library(MicroarrayMethods)
# Define function arguments
celfiles_path <- "~/Área de Trabalho/exp1/"
pheno_data <- "samples.txt"
sep <- "\t"
group <- "group"
type <- NULL
batch <- "batch"
report_output <- "~/Área de Trabalho/QC12312.html"
dataset <- "hsapiens_gene_ensembl"
platform <- "affy_hg_u133_plus_2"
ref_col <- "hgnc_symbol"
contrasts <- c(s8xs0 = "shOTX2_8-shOTX2_0", s16xs8 = "shOTX2_16-shOTX2_8", s24xs16 = "shOTX2_24-shOTX2_16",
s48xs24 = "shOTX2_48-shOTX2_24", s96xs48 = "shOTX2_96-shOTX2_48")
# Quality control report
create_report(celfiles = celfiles_path,
pheno_data = pheno_data,
sep = sep,
components = c(1,2),
group = group,
batch = batch, output_file = report_output)
# Import and normalize
eset <- import_norm(celfiles_path = celfiles_path, pheno_data = pheno_data, sep = sep)
# Get probes annotation
feature_data <- get_annotation(dataset = dataset, platform = platform)
# Set annotation into eset and remove promiscuous probes and dual notations
eset <- set_fdata(eset, feature_data,
probe_col = platform,
ref_col = ref_col,
rm_probes = TRUE)
# Differential expression
delimma <- diff_exp(eset, contrasts, method = "global", adjust.method = "BH", p.value = 0.001, degenes_only = T)
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