add function rnaseqqc()

	}

}

rnaseqqc <- function(

				count_file,

				sample = NA,

				group = NA,

				organism = "human",

				count_type = "star",

				plot_type = "mds"

){

	g.number <- length(group)

	if(g.number != length(count_file)){

		stop()

	}else{

		g.color <- as.factor(group)

		if(g.number <= 10){

			levels(g.color) <- sample(chaos_color(),g.number)

		}else{

			levels(g.color) <- colorRampPalette(chaos_color())(n)

		}

		g.color <- as.character(g.color)

	}

	if(is.na(sample) | length(sample) != length(count_file)){

		sample <- gsub("_ReadsPerGene.out.tab","",count_file)

	}

	if(tolower(count_type) == "star"){

		cols <- c(1, 2)

		header_str <- TRUE

		skip_rows <- 4

	}else if(tolower(count_type) == "featurecounts")

	{

		cols <- c(1, 7)

		header_str <- FALSE

		skip_rows <- 1

	}

	x <-	readDGE(

				count_file,

				columns = cols,

				header = header_str,

				skip = skip_rows

			) %>% 

			.[

				filterByExpr(.), 

				keep.lib.sizes = F

			] |>

			calcNormFactors(method = "TMM") |>

			cpm(log = T)

	if(plot_type == "mds"){

		plotMDS(x, labels = sample,col = g.color)

	}else if(plot_type == "glmds"){

		Glimma::glMDSPlot(x, labels = sample, launch = F,groups = group)

		print("figure saved in ./glimma-plots")

	}

}

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