Plot sample coefficient of variation whitin group
plot_cvs.RdPlot sample coefficient of variation whitin group
Value
a histogram plot of row coefficient of variation (standard deviation / mean) in each condition
Examples
data(Silicosis_pg)
data <- Silicosis_pg
data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")
# Differential test
ecols <- grep("LFQ.", colnames(data_unique))
se <- make_se_parse(data_unique, ecols,mode = "delim")
filt <- filter_se(se, thr = 0, fraction = 0.4, filter_formula = ~ Reverse != "+" & Potential.contaminant!="+")
#> filter base on missing number is <= 0 in at least one condition.
#> filter base on missing number fraction < 0.4 in each row
#> filter base on giving formula
norm <- normalize_vsn(filt)
#> vsn2: 8762 x 20 matrix (1 stratum).
#> Please use 'meanSdPlot' to verify the fit.
imputed <- impute(norm, fun = "MinProb", q = 0.05)
#> Imputing along margin 2 (samples/columns).
#> [1] 0.3026531
plot_cvs(imputed)
