Lolliplot-class {GenVisR} | R Documentation

## Class Lolliplot

### Description

An S4 class for the lolliplot object, under development!!!

### Usage

    Lolliplot(
      input,
      transcript = NULL,
      species = "hsapiens",
      host = "www.ensembl.org",
      txdb = NULL,
      BSgenome = NULL,
      emphasize = NULL,
      DomainPalette = NULL,
      MutationPalette = NULL,
      labelAA = TRUE,
      plotALayers = NULL,
      plotBLayers = NULL,
      sectionHeights = NULL,
      verbose = FALSE
    )

### Arguments

`input` | Object of class MutationAnnotationFormat, GMS, VEP, or a data.table with appropriate columns
`transcript` | Character string specifying the ensembl transcript for which to plot, should be a transcript which corresponds to the gene parameter.
`species` | Character string specifying a species when using biomaRt queries
`host` | Character string specifying a host to connect to when using biomaRt queries
`txdb` | A bioconoductor txdb object to annotate amino acid positions, required only if amino acid changes are missing (see details).
`BSgenome` | A bioconductor BSgenome object to annotate amino acid positions, required only if amino acid changes are missing (see details).
`emphasize` | Character vector specifying a list of mutations to emphasize.
`DomainPalette` | Character vector specifying the colors used for encoding protein domains
`MutationPalette` | Character vector specifying the colors used for encoding mutations
`labelAA` | Boolean specifying if labels should be added to emphasized mutations
`plotALayers` | list of ggplot2 layers to be passed to the density plot.
`plotBLayers` | list of ggplot2 layers to be passed to the lolliplot.
`sectionHeights` | Numeric vector specifying relative heights of each plot section, should sum to one. Expects a value for each section.
`verbose` | Boolean specifying if status messages should be reported.

### Slots

`PlotA`

  gtable object for the top sub-plot

`PlotB`

  gtable object for the bottom sub-plot

`Grob`

  gtable object storing the arranged plot

`primaryData`

  data.table object storing the primary data

`geneData`

  data.table object storing gene and domain coordinates

### Examples

    # Load a pre-existing data set
    dataset <- PIK3CA

    # mode 1, amino acid changes are not present

    library(TxDb.Hsapiens.UCSC.hg38.knownGene)
    library(BSgenome.Hsapiens.UCSC.hg38)
    txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene
    BSgenome <- BSgenome.Hsapiens.UCSC.hg38

    keep <- c("Chromosome", "Start_Position", "End_Position", "Reference_Allele",
              "Tumor_Seq_Allele2", "Tumor_Sample_Barcode", "Gene", "Variant_Classification")
    dataset.mode1 <- dataset[,keep]
    colnames(dataset.mode1) <- c("chromosome", "start", "stop", "reference", "variant",
                                 "sample", "gene", "consequence")

    # mode 2, amino acid changes are present

    keep <- c("Chromosome", "Start_Position", "End_Position", "Reference_Allele",
              "Tumor_Seq_Allele2", "Tumor_Sample_Barcode", "Gene", "Variant_Classification",
              "Transcript_ID", "HGVSp")
    dataset.mode2 <- dataset[,keep]
    colnames(dataset.mode2) <- c("chromosome", "start", "stop", "reference", "variant",
                                 "sample", "gene", "consequence", "transcript", "proteinCoord")

    # run Lolliplot

    object <- Lolliplot(dataset.mode1, transcript="ENST00000263967",
                        species="hsapiens", txdb=txdb, BSgenome=BSgenome)
    object <- Lolliplot(dataset.mode2, transcript="ENST00000263967",
                        species="hsapiens")

[Package GenVisR version 1.20.0 Index]