| demo_desq_out | R Documentation |
The output dummy data for "RNA" meythod illustrating purpose.
The data includes 10 columns.
- treated1fb:
- treated2fb:
- treated3fb:
- untreated1fb:
- untreated2fb:
- untreated3fb:
- untreated4fb:
This data contains 8166 rows and 7 columns.
Please check the vignette "metevalue" for details.
# library("pasilla")
# pasCts <- system.file("extdata",
# "pasilla_gene_counts.tsv",
# package="pasilla", mustWork=TRUE)
# pasAnno <- system.file("extdata",
# "pasilla_sample_annotation.csv",
# package="pasilla", mustWork=TRUE)
# cts <- as.matrix(read.csv(pasCts,sep="\t",row.names="gene_id"))
# coldata <- read.csv(pasAnno, row.names=1)
# coldata <- coldata[,c("condition","type")]
# coldata$condition <- factor(coldata$condition)
# coldata$type <- factor(coldata$type)
#
# library("DESeq2")
# colnames(cts)=paste0(colnames(cts),'fb')
# cts = cts[,rownames(coldata)]
# dds <- DESeqDataSetFromMatrix(countData = cts,
# colData = coldata,
# design = ~ condition)
# dds <- DESeq(dds)
#
#
# dat <- t(t(cts)/(dds$sizeFactor))
# dat.out <- dat[rowSums(dat >5)>=0.8*ncol(dat),]
#
# demo_desq_out <- log(dat.out)
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