degall: Differential Expression analysis using all combination

Description Usage Arguments Value Examples

View source: R/degall.R

Description

split count data with index and Differential expression analysis of all comination groups.

Usage

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degall(dat, idx, normalized, meth_norm, param_fdr)

Arguments

dat

dataframe: RNA-seq count table. row: samples, column: genes

idx

factor: group of data. E.g. factor(c(1,1,2,2)); factor(c('A','A','B','B'))

normalized

logical: The 'dat' is a normalized count data or not.

meth_norm

integer: Choose from the six pipe line numbers below 1:'DEGES/TbT', 2:'DEGES/edgeR', 3:'iDEGES/edgeR', 4: 'DEGES/DESeq', 5: iDEGES/DESeq, 6: iDEGES/DESeq2. The default value is 2

param_fdr

numeric: fdr value.

Value

ggplot object which containing result of 'TCC::estimateDE', without normalized count data.

Examples

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# # sample data of rna-seq
# fpkm_rep3 <- rskodat::fpkm
# fpkm_rep2 <- rskodat::fpkm[c(1,2,4,5)]
# fpkm_norep <- rskodat::fpkm[c(1,4)]
#
# # aruguments
# gp <- sapply(strsplit(names(fpkm_rep3), "_"), function(x) paste(x[1:2], collapse = "_"))
# index0 <- factor(rep(1:4, each = 3))
# index1 <- factor(gp, levels=unique(gp))
# index2 <-factor(rep(1:2, each=2))
# index3 <- factor(c(1, 2))
#
## multi-group with replicate
# res1a <- rskoseq::degall(dat = fpkm_rep3, idx = index0, meth_norm = 2)
# res1b <- rskoseq::degall(dat = fpkm_rep3, idx = index1, meth_norm = 4)
#
# #' # two-group with replicate
# res2a <- rskoseq::degall(dat = fpkm_rep2, idx = index2, meth_norm = 1)
# res2b <- rskoseq::degall(dat = fpkm_rep2, idx = index2, meth_norm = 2)
# res2c <- rskoseq::degall(dat = fpkm_rep2, idx = index2, meth_norm = 3)
# res2d <- rskoseq::degall(dat = fpkm_rep2, idx = index2, meth_norm = 4)
# res2e <- rskoseq::degall(dat = fpkm_rep2, idx = index2, meth_norm = 5)
# res2f <- rskoseq::degall(dat = fpkm_rep2, idx = index2, meth_norm = 6)
#
# # two samples without replicate
# res3a <- rskoseq::degall(dat = fpkm_norep, idx = index3, meth_norm = 3)
# res3b <- rskoseq::degall(dat = fpkm_norep, idx = index3, meth_norm = 4)
#
## get result of estimateDE
# head(res1a$deg)
#
## redraw MA-plot
# tmp <- res1a$deg %>% filter(comp %in% levels(.$comp)[1:3])
# add_de <- res1a$num_deg %>% filter(comp %in% levels(.$comp)[1:3])
#
# ggplot2::ggplot(tmp, ggplot2::aes(x = a.value, y = m.value, colour = fct)) +
#   ggplot2::geom_point(size = 0.3) +
#   ggplot2::scale_color_manual(values =
#     c("non-DEG"="#BEBEBE80", "up"="#FF000080", "down" ="#0000FF80")) +
#   ggplot2::theme_minimal(base_size = 15) +
#   ggplot2::labs(x = "A=(log2(G2)+log2(G1))/2", y = "M=log2(G2)-log2(G1)", colour = "") +
#   ggplot2::theme(legend.position = "top") +
#   ggplot2::guides(colour = ggplot2::guide_legend(override.aes = list(alpha=1, size = 5))) +
#   ggplot2::geom_text(data = add_de, ggplot2::aes(x = x, y = y, label = value, colour = key),
#     size = 5, show.legend = F) +
#   ggplot2::facet_wrap(~comp, ncol = 3)

shkonishi/rskoseq documentation built on Dec. 24, 2018, 3:14 a.m.