R: draw an oncoplot

oncoplot {maftools}

R Documentation

draw an oncoplot

Description

takes output generated by read.maf and draws an oncoplot

Usage

oncoplot(
  maf,
  top = 20,
  genes = NULL,
  altered = FALSE,
  mutsig = NULL,
  mutsigQval = 0.1,
  drawRowBar = TRUE,
  drawColBar = TRUE,
  includeColBarCN = TRUE,
  draw_titv = FALSE,
  logColBar = FALSE,
  clinicalFeatures = NULL,
  pathways = NULL,
  exprsTbl = NULL,
  additionalFeature = NULL,
  additionalFeaturePch = 20,
  additionalFeatureCol = "gray70",
  additionalFeatureCex = 0.9,
  annotationDat = NULL,
  annotationColor = NULL,
  genesToIgnore = NULL,
  showTumorSampleBarcodes = FALSE,
  barcode_mar = 4,
  gene_mar = 5,
  legend_height = 4,
  removeNonMutated = TRUE,
  fill = TRUE,
  cohortSize = NULL,
  colors = NULL,
  sortByMutation = FALSE,
  sortByAnnotation = FALSE,
  numericAnnoCol = NULL,
  groupAnnotationBySize = TRUE,
  annotationOrder = NULL,
  keepGeneOrder = FALSE,
  GeneOrderSort = TRUE,
  sampleOrder = NULL,
  writeMatrix = FALSE,
  sepwd_genes = 0.5,
  sepwd_samples = 0.25,
  fontSize = 0.8,
  SampleNamefontSize = 1,
  showTitle = TRUE,
  titleText = NULL,
  titleFontSize = 1.5,
  legendFontSize = 1.2,
  annotationFontSize = 1.2,
  bgCol = "#CCCCCC",
  borderCol = "white",
  colbar_pathway = FALSE
)

Arguments

`maf`	an `MAF` object generated by `read.maf`
`top`	how many top genes to be drawn. defaults to 20.
`genes`	Just draw oncoplot for these genes. Default NULL.
`altered`	Default FALSE. Chooses top genes based on muatation status. If `TRUE` chooses top genes based alterations (CNV or mutation).
`mutsig`	Mutsig resuts if availbale. Usually file named sig_genes.txt If provided plots significant genes and correpsonding Q-values as side row-bar. Default NULL.
`mutsigQval`	Q-value to choose significant genes from mutsig results. Default 0.1
`drawRowBar`	logical plots barplot for each gene. Default `TRUE`.
`drawColBar`	logical plots barplot for each sample. Default `TRUE`.
`includeColBarCN`	Whether to include CN in column bar plot. Default TRUE
`draw_titv`	logical Includes TiTv plot. `FALSE`
`logColBar`	Plot top bar plot on log10 scale. Default `FALSE`.
`clinicalFeatures`	columns names from 'clinical.data' slot of `MAF` to be drawn in the plot. Dafault NULL.
`pathways`	Default 'NULL'. Can be 'auto', or a two column data.frame/tsv-file with genes and correspoding pathway mappings.'
`exprsTbl`	Expression values if availble. Must be a data.frame with two columns containing to gene names and expression values.
`additionalFeature`	a vector of length two indicating column name in the MAF and the factor level to be highlighted. Provide a list of values for highlighting more than one features
`additionalFeaturePch`	Default 20
`additionalFeatureCol`	Default "gray70"
`additionalFeatureCex`	Default 0.9
`annotationDat`	If MAF file was read without clinical data, provide a custom `data.frame` with a column `Tumor_Sample_Barcode` containing sample names along with rest of columns with annotations. You can specify which columns to be drawn using 'clinicalFeatures' argument.
`annotationColor`	Custom colors to use for 'clinicalFeatures'. Must be a named list containing a named vector of colors. Default NULL. See example for more info.
`genesToIgnore`	do not show these genes in Oncoplot. Default NULL.
`showTumorSampleBarcodes`	logical to include sample names.
`barcode_mar`	Default 4
`gene_mar`	Default 5
`legend_height`	Height of plotting area for legend. Default 4
`removeNonMutated`	Logical. If `TRUE` removes samples with no mutations in the oncoplot for better visualization. Default `TRUE`.
`fill`	Logical. If `TRUE` draws genes and samples as blank grids even when they are not altered.
`cohortSize`	Number of sequenced samples in the cohort. Default all samples from Cohort. You can manually specify the cohort size. Default `NULL`
`colors`	named vector of colors for each Variant_Classification.
`sortByMutation`	Force sort matrix according mutations. Helpful in case of MAF was read along with copy number data. Default FALSE.
`sortByAnnotation`	logical sort oncomatrix (samples) by provided 'clinicalFeatures'. Sorts based on first 'clinicalFeatures'. Defaults to FALSE. column-sort
`numericAnnoCol`	color palette used for numeric annotations. Default 'YlOrBr' from RColorBrewer
`groupAnnotationBySize`	Further group 'sortByAnnotation' orders by their size. Defaults to TRUE. Largest groups comes first.
`annotationOrder`	Manually specify order for annotations. Works only for first 'clinicalFeatures'. Default NULL.
`keepGeneOrder`	logical whether to keep order of given genes. Default FALSE, order according to mutation frequency
`GeneOrderSort`	logical this is applicable when 'keepGeneOrder' is TRUE. Default TRUE
`sampleOrder`	Manually speify sample names for oncolplot ordering. Default NULL.
`writeMatrix`	writes character coded matrix used to generate the plot to an output file.
`sepwd_genes`	Default 0.5
`sepwd_samples`	Default 0.25
`fontSize`	font size for gene names. Default 0.8.
`SampleNamefontSize`	font size for sample names. Default 1
`showTitle`	Default TRUE
`titleText`	Custom title. Default 'NULL'
`titleFontSize`	font size for title. Default 1.5
`legendFontSize`	font size for legend. Default 1.2
`annotationFontSize`	font size for annotations. Default 1.2
`bgCol`	Background grid color for wild-type (not-mutated) samples. Default gray - "#CCCCCC"
`borderCol`	border grid color (not-mutated) samples. Default 'white'.
`colbar_pathway`	Draw top column bar with respect to diplayed pathway. Default FALSE.

Details

Takes maf file as input and plots it as a matrix. Any desired clincal features can be added at the bottom of the oncoplot by providing clinicalFeatures. Oncoplot can be sorted either by mutations or by clinicalFeatures using arguments sortByMutation and sortByAnnotation respectively.

Value

None.

Examples

laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
laml.clin = system.file('extdata', 'tcga_laml_annot.tsv', package = 'maftools')
laml <- read.maf(maf = laml.maf, clinicalData = laml.clin)
#Basic onocplot
oncoplot(maf = laml, top = 3)
#Changing colors for variant classifications (You can use any colors, here in this example we will use a color palette from RColorBrewer)
col = RColorBrewer::brewer.pal(n = 8, name = 'Paired')
names(col) = c('Frame_Shift_Del','Missense_Mutation', 'Nonsense_Mutation', 'Multi_Hit', 'Frame_Shift_Ins',
               'In_Frame_Ins', 'Splice_Site', 'In_Frame_Del')
#Color coding for FAB classification; try getAnnotations(x = laml) to see available annotations.
fabcolors = RColorBrewer::brewer.pal(n = 8,name = 'Spectral')
names(fabcolors) = c("M0", "M1", "M2", "M3", "M4", "M5", "M6", "M7")
fabcolors = list(FAB_classification = fabcolors)
oncoplot(maf = laml, colors = col, clinicalFeatures = 'FAB_classification', sortByAnnotation = TRUE, annotationColor = fabcolors)

[Package maftools version 2.3.30 Index]