`plotNA-methods.Rd`

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.

- 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.

See also the `filterNA`

method to filter out features with
a specified proportion if missing values.

```
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)
```