Exploring missing data in 'MSnSet' instances

These methods produce plots that illustrate missing data.

is.na returns the expression matrix of it MSnSet argument as a matrix of logicals referring whether the corresponding cells are NA or not. It is generally used in conjunction with table and image (see example below).

The plotNA method produces plots that illustrate missing data. The completeness of the full dataset or a set of proteins (ordered by increasing NA content along the x axis) is represented. The methods make use the ggplot2 system. An object of class 'ggplot' is returned invisibly.

Methods

is.na

signature(x = "MSnSet") Returns the a matrix of logicals of dimensions dim(x) specifiying if respective values are missing in the MSnSet's expression matrix.

plotNA

signature(object = "MSnSet", pNA = "numeric") Plots missing data for an MSnSet instance. pNA is a numeric of length 1 that specifies the percentage of accepted missing data values per features. This value will be highlighted with a point on the figure, illustrating the overall percentage of NA values in the full data set and the number of proteins retained. Default is 1/2.

Author

Laurent Gatto

See also

See also the filterNA method to filter out features with a specified proportion if missing values.

Examples

data(msnset)
exprs(msnset)[sample(prod(dim(msnset)), 120)] <- NA

head(is.na(msnset))
#>     iTRAQ4.114 iTRAQ4.115 iTRAQ4.116 iTRAQ4.117
#> X1        TRUE       TRUE       TRUE      FALSE
#> X10       TRUE       TRUE      FALSE      FALSE
#> X11      FALSE      FALSE       TRUE       TRUE
#> X12      FALSE      FALSE      FALSE       TRUE
#> X13      FALSE       TRUE      FALSE       TRUE
#> X14      FALSE      FALSE       TRUE       TRUE
table(is.na(msnset))
#> 
#> FALSE  TRUE 
#>    99   121 
image(msnset)


plotNA(msnset, pNA = 1/4)