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

oncoplot

R Documentation

draw an oncoplot

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,
  leftBarVline = NULL,
  leftBarVlineCol = "gray70",
  rightBarData = NULL,
  rightBarLims = NULL,
  rightBarVline = NULL,
  rightBarVlineCol = "gray70",
  topBarData = NULL,
  topBarLims = NULL,
  topBarHline = NULL,
  topBarHlineCol = "gray70",
  logColBar = FALSE,
  includeColBarCN = TRUE,
  clinicalFeatures = NULL,
  annotationColor = NULL,
  annotationDat = NULL,
  pathways = NULL,
  topPathways = 3,
  path_order = NULL,
  selectedPathways = NULL,
  collapsePathway = FALSE,
  pwLineCol = "#535c68",
  pwLineWd = 1,
  draw_titv = FALSE,
  titv_col = NULL,
  showTumorSampleBarcodes = FALSE,
  tsbToPIDs = NULL,
  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 = FALSE,
  fill = TRUE,
  cohortSize = NULL,
  colors = NULL,
  cBioPortal = FALSE,
  bgCol = "#ecf0f1",
  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,
  showPct = TRUE
)

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'.
`leftBarVline`	Draw vertical lines at these values. Default 'NULL'.
`leftBarVlineCol`	Line color for 'leftBarVline' Default gray70
`rightBarData`	Data for rightside barplot. Must be a data.frame with two columns containing to gene names and values. Default 'NULL' which draws distribution by variant classification. This option is applicable when only 'drawRowBar' is TRUE.
`rightBarLims`	limits for 'rightBarData'. Default 'NULL'.
`rightBarVline`	Draw vertical lines at these values. Default 'NULL'.
`rightBarVlineCol`	Line color for 'rightBarVline' Default gray70
`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 containing sample names and values for each sample. This option is applicable when only 'drawColBar' is TRUE.
`topBarLims`	limits for 'topBarData'. Default 'NULL'.
`topBarHline`	Draw horizontal lines at these values. Default 'NULL'.
`topBarHlineCol`	Line color for 'topBarHline.' Default gray70
`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. Default 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 'sigpw', 'smgbp', or a two column data.frame/tsv-file with genes and corresponding pathway mappings.'
`topPathways`	Top most altered pathways to draw. Default 3. Mutually exclusive with 'selectedPathways'
`path_order`	Default 'NULL' Manually specify the order of pathways
`selectedPathways`	Manually provide the subset of pathway names to be selected from 'pathways'. Default NULL. In case 'pathways' is 'auto' draws top 3 altered pathways.
`collapsePathway`	Shows only rows corresponding to the pathways. Default FALSE.
`pwLineCol`	Color for the box around the pathways Default #535c68
`pwLineWd`	Line width for the box around the pathways Default Default 1
`draw_titv`	logical Includes TiTv plot. `FALSE`
`titv_col`	named vector of colors for each transition and transversion classes. Should be of length six with the names "C>T" "C>G" "C>A" "T>A" "T>C" "T>G". Default NULL.
`showTumorSampleBarcodes`	logical to include sample names.
`tsbToPIDs`	Custom names for Tumor_Sample_Barcodes. Can be a column name in clinicaldata or a 2 column data.frame of Tumor_Sample_Barcodes to patient ID mappings. Applicable only when 'showTumorSampleBarcodes = TRUE'. Default NULL.
`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 `FALSE`.
`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.
`cBioPortal`	Adds annotations similar to cBioPortals MutationMapper and collapse Variants into Truncating and rest.
`bgCol`	Background grid color for wild-type (not-mutated) samples. Default "#ecf0f1"
`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'
`showPct`	Default TRUE. Shows percent altered to the right side of the plot.

Details

Takes an MAF object as an 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.

By setting 'pathways' argument either 'sigpw' or 'smgbp' - cohort can be summarized by altered pathways. pathways argument also accepts a custom pathway list in the form of a two column tsv file or a data.frame containing gene names and their corresponding pathway.

Value

Invisibly returns a list with components 1. 'oncomatrix' A matrix used for drawing the oncoplot. Values are numeric coded for each variant classification 2. 'vc_legend' A mapping of variant classification to numeric values in the oncomatrix 3. 'vc_color' Color coding used for each variant classification

References

Bailey, Matthew H et al. “Comprehensive Characterization of Cancer Driver Genes and Mutations.” Cell vol. 173,2 (2018): 371-385.e18. doi:10.1016/j.cell.2018.02.060 Sanchez-Vega, Francisco et al. “Oncogenic Signaling Pathways in The Cancer Genome Atlas.” Cell vol. 173,2 (2018): 321-337.e10. doi:10.1016/j.cell.2018.03.035

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)

PoisonAlien/maftools documentation built on Nov. 10, 2024, 6:01 p.m.