| DrawParamPerModBaseCategories | R Documentation |
Return boxplots describing, for each feature provided, the distribution of a parameter provided by categories of counts (or counts per KiloBase pairs (kbp)) of the base modified (Mod) and the base letter of the modified base (Base). These categories should have a comparable amount of Mod (or Base) between them. Example: for Mod="6mA", Base="A"; for Mod="5mC", Base="C".
DrawParamPerModBaseCategories( grangesAnnotationsWithCounts, cParamColname, cParamFullName = cParamColname, cParamYLabel = cParamColname, cSelectFeature = NULL, lUseCountsPerkbp = TRUE, lKeepOutliers = FALSE, lUseSameYAxis = FALSE, cBaseMotif, cModMotif, lBoxPropToCount = TRUE )
grangesAnnotationsWithCounts |
A GRanges object based on grangesAnnotations with the counts:
The Genomic features categories must be in a column named "type". |
cParamColname |
Name of the column, in the grangesAnnotationsWithCounts provided, containing the parameter to be compared with Mod|Base categories. |
cParamFullName |
Name of the parameter to be displayed in the title of the plot. Defaults to cParamColname. |
cParamYLabel |
Name of the parameter to be displayed on the Y-axis of the plot. Defaults to cParamColname. |
cSelectFeature |
The name of the feature from the annotation to be analysed along counts and parameter provided. Defaults to NULL (No subsetting: counts and parameter provided from all features in the annotation provided will be used). |
lUseCountsPerkbp |
If TRUE, use counts per kbp (Modcount_perkbp and Basecount_perkbp) to calculate the Mod|Base categories to be displayed. If FALSE, use counts (Modcount and Basecount) to calculate the Mod|Base categories to be displayed. Defaults to TRUE. |
lKeepOutliers |
If FALSE, remove outliers before plotting. Defaults to FALSE. |
lUseSameYAxis |
If TRUE, the 2 plots will use the same range for the y-axis. If FALSE, y-axis of the 2 plots will be independant. Defaults to FALSE. |
cBaseMotif |
The name of the motif with the base letter of the modified base. |
cModMotif |
The name of the motif with the modification in the output. |
lBoxPropToCount |
If TRUE, the width of each boxplot depends on the number of Mod (or Base) in the categories. If FALSE, all boxplots will have the same size. Defaults to TRUE. |
# loading genome
myGenome <- Biostrings::readDNAStringSet(system.file(
package = "DNAModAnnot", "extdata",
"ptetraurelia_mac_51_sca171819.fa"
))
# loading annotation
library(rtracklayer)
myAnnotations <- readGFFAsGRanges(system.file(
package = "DNAModAnnot", "extdata",
"ptetraurelia_mac_51_annotation_v2.0_sca171819.gff3"
))
# Preparing a grangesPacBioGFF and a grangesPacBioCSV datasets
myGrangesPacBioGFF <-
ImportPacBioGFF(
cPacBioGFFPath = system.file(
package = "DNAModAnnot", "extdata",
"ptetraurelia.modifications.sca171819.gff"
),
cNameModToExtract = "m6A",
cModNameInOutput = "6mA",
cContigToBeAnalyzed = names(myGenome)
)
myGposPacBioCSV <-
ImportPacBioCSV(
cPacBioCSVPath = system.file(
package = "DNAModAnnot", "extdata",
"ptetraurelia.bases.sca171819.csv"
),
cSelectColumnsToExtract = c(
"refName", "tpl", "strand", "base",
"score", "ipdRatio", "coverage"
),
lKeepExtraColumnsInGPos = TRUE, lSortGPos = TRUE,
cContigToBeAnalyzed = names(myGenome)
)
myGposPacBioCSV <- myGposPacBioCSV[myGposPacBioCSV$base == "A"]
# Retrieve annotations with "Mod" and "Base" counts (and counts per kbp)
myAnn_ModBase_counts <- GetModBaseCountsByFeature(
grangesAnnotations = myAnnotations,
grangesModPos = myGrangesPacBioGFF,
gposModTargetBasePos = myGposPacBioCSV
)
# Add Parameter by feature to annotation file
myAnn_ModBase_counts$ParamToPlot <- width(myAnn_ModBase_counts)
DrawParamPerModBaseCategories(myAnn_ModBase_counts,
cParamColname = "ParamToPlot",
cParamFullName = "Gene Width",
cParamYLabel = "Gene Width (bp)",
cSelectFeature = c("gene"),
lUseCountsPerkbp = TRUE,
lKeepOutliers = FALSE,
lUseSameYAxis = FALSE,
cBaseMotif = "A",
cModMotif = "6mA",
lBoxPropToCount = FALSE
)
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