To compare data of different samples, a ModifierSet can be used. To select the data alongside the transcripts and their positions a GRanges or a GRangesList needs to be provided. In case of a GRanges object, the parent column must match the transcript names as defined by the out put of ranges(x), whereas in case of a GRangesList the element names must match the transcript names.

compare(x, name, pos = 1L, ...)

compareByCoord(x, coord, ...)

plotCompare(x, name, pos = 1L, normalize, ...)

plotCompareByCoord(x, coord, normalize, ...)

# S4 method for ModifierSet
compare(x, name, pos = 1L, normalize, ...)

# S4 method for ModifierSet,GRanges
compareByCoord(x, coord, normalize, ...)

# S4 method for ModifierSet,GRangesList
compareByCoord(x, coord, normalize, ...)

# S4 method for ModifierSet
plotCompare(x, name, pos = 1L, normalize, ...)

# S4 method for ModifierSet,GRanges
plotCompareByCoord(x, coord, normalize, ...)

# S4 method for ModifierSet,GRangesList
plotCompareByCoord(x, coord, normalize, ...)

Arguments

x

a Modifier or ModifierSet object.

name

Only for compare: the transcript name

pos

Only for compare: pos for comparison

...

optional parameters:

  • alias a data.frame with two columns, tx_id and name, to convert transcipt ids to another identifier

  • name Limit results to one specific gene or transcript

  • sequenceData TRUE or FALSE? Should the aggregate of sequenceData be used for the comparison instead of the aggregate data if each Modifier element? (default: sequenceData = FALSE)

  • compareType a valid score type to use for the comparison. If sequenceData = FALSE this defaults to mainScore(x), whereas if sequenceData = TRUE all columns will be used by setting allTypes = TRUE.

  • allTypes TRUE or FALSE? Should all available score be compared? (default: allTypes = sequenceData)

  • ... passed on to subsetByCoord

coord

coordinates of position to subset to. Either a GRanges or a GRangesList object. For both types the 'Parent' column is expected to match the transcript name. The GRangesList object is unlisted and only non duplicated entries are retained.

normalize

either a single logical or character value. If it is a character, it must match one of the names in the ModifierSet.

Value

compareByCoord returns a

DataFrame and

plotCompareByCoord returns a ggplot object, which can be modified further. The DataFrame contains columns per sample as well as the columns names, positions and mod incorporated from the coord input. If coord contains a column

Activity this is included in the results as well.

Examples

data(msi,package="RNAmodR")
# constructing a GRanges obejct to mark positive positions
mod <- modifications(msi)
coord <- unique(unlist(mod))
coord$score <- NULL
coord$sd <- NULL
# return a DataFrame
compareByCoord(msi,coord)
#> DataFrame with 6 rows and 6 columns
#>   SampleSet1 SampleSet2 SampleSet3    names positions         mod
#>    <numeric>  <numeric>  <numeric> <factor>  <factor> <character>
#> 1   0.900932   0.998134   0.953651       2         34           I
#> 2   0.899622   0.856241   0.976928       4         35           I
#> 3   0.984035   0.992012   0.993128       6         34           I
#> 4   0.934553   0.942905   0.943773       7         67           I
#> 5   0.709758   0.766484   0.681451       9         7            I
#> 6   0.874027   0.971474   0.954782       11        35           I
# plot the comparison as a heatmap
plotCompareByCoord(msi,coord)