oncoplot: draw an oncoplot
In thesushantpatil/maftools: Summarize, Analyze and Visualize MAF Files

Description Usage Arguments Details Value See Also Examples

takes output generated by read.maf and draws an oncoplot

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

`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).
`drawRowBar`	logical. Plots righ barplot for each gene. Default `TRUE`.
`drawColBar`	logical plots top barplot for each sample. Default `TRUE`.
`leftBarData`	Data for leftside barplot. Must be a data.frame with two columns containing gene names and values. Default 'NULL'
`leftBarLims`	limits for 'leftBarData'. Default 'NULL'.
`rightBarData`	Data for rightside barplot. Must be a data.frame with two columns containing to gene names and values. Default 'NULL' which draws distibution by variant classification. This option is applicable when only 'drawRowBar' is TRUE.
`rightBarLims`	limits for 'rightBarData'. Default 'NULL'.
`topBarData`	Default 'NULL' which draws absolute number of mutation load for each sample. Can be overridden by choosing one clinical indicator(Numeric) or by providing a two column data.frame contaning sample names and values for each sample. This option is applicable when only 'drawColBar' is TRUE.
`logColBar`	Plot top bar plot on log10 scale. Default `FALSE`.
`includeColBarCN`	Whether to include CN in column bar plot. Default TRUE
`clinicalFeatures`	columns names from 'clinical.data' slot of `MAF` to be drawn in the plot. Dafault NULL.
`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.
`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.
`pathways`	Default 'NULL'. Can be 'auto', or a two column data.frame/tsv-file with genes and correspoding pathway mappings.'
`selectedPathways`	Manually provide the subset of pathway names to be seletced from 'pathways'. Default NULL. In case 'pathways' is 'auto' draws top 3 altered pathways.
`draw_titv`	logical Includes TiTv plot. `FALSE`
`showTumorSampleBarcodes`	logical to include sample names.
`barcode_mar`	Margin width for sample names. Default 4
`gene_mar`	Margin width for gene names. Default 5
`anno_height`	Height of plotting area for sample annotations. Default 1
`legend_height`	Height of plotting area for legend. Default 4
`sortByAnnotation`	logical sort oncomatrix (samples) by provided 'clinicalFeatures'. Sorts based on first 'clinicalFeatures'. Defaults to FALSE. column-sort
`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.
`sortByMutation`	Force sort matrix according mutations. Helpful in case of MAF was read along with copy number data. Default FALSE.
`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.
`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
`genesToIgnore`	do not show these genes in Oncoplot. Default NULL.
`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.
`bgCol`	Background grid color for wild-type (not-mutated) samples. Default gray - "#CCCCCC"
`borderCol`	border grid color (not-mutated) samples. Default 'white'.
`numericAnnoCol`	color palette used for numeric annotations. Default 'YlOrBr' from RColorBrewer
`drawBox`	logical whether to draw a box around main matrix. Default FALSE
`fontSize`	font size for gene names. Default 0.8.
`SampleNamefontSize`	font size for sample names. Default 1
`titleFontSize`	font size for title. Default 1.5
`legendFontSize`	font size for legend. Default 1.2
`annotationFontSize`	font size for annotations. Default 1.2
`sepwd_genes`	size of lines seperating genes. Default 0.5
`sepwd_samples`	size of lines seperating samples. Default 0.25
`writeMatrix`	writes character coded matrix used to generate the plot to an output file.
`colbar_pathway`	Draw top column bar with respect to diplayed pathway. Default FALSE.
`showTitle`	Default TRUE
`titleText`	Custom title. Default 'NULL'

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.

None.

oncostrip

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)