oncoplot: draw an oncoplot

In maftools: Summarize, Analyze and Visualize MAF Files

Description

takes output generated by read.maf and draws an oncoplot

Usage

oncoplot(
  maf,
  top = 20,
  minMut = NULL,
  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,
  barcodeSrt = 90,
  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",
  annoBorderCol = NA,
  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
)

Arguments

maf	an MAF object generated by read.maf
top	how many top genes to be drawn. defaults to 20.
minMut	draw all genes with 'min' number of mutations. Can be an integer or fraction (of samples mutated), Default NULL
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
barcodeSrt	Rotate sample labels. Default 90.
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'.
annoBorderCol	border grid color for annotations. Default NA.
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'

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.

See Also

oncostrip

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)

Example output

-Reading
-Validating
-Silent variants: 475 
-Summarizing
-Processing clinical data
-Finished in 0.715s elapsed (0.651s cpu) 

maftools documentation built on Feb. 6, 2021, 2 a.m.