g3viz (version 0.1.4)

g3Lollipop: G3Lollipop diagram for mutation data

Description

Generate G3Lollipop chart from the given mutation data.

Usage

g3Lollipop(mutation.dat, gene.symbol, uniprot.id = NA,
  gene.symbol.col = "Hugo_Symbol", aa.pos.col = "AA_Position",
  protein.change.col = c("Protein_Change", "HGVSp_Short"),
  factor.col = "Mutation_Class", plot.options = list())

Arguments

mutation.dat

Mutation data frame.

gene.symbol

HGNC gene symbol.

uniprot.id

UniProt ID, in case that gene symbol maps to multiple UniProt entries.

gene.symbol.col

Column name of Hugo gene symbols (e.g., TP53). Default Hugo_Symbol.

aa.pos.col

Column name of the parsed amino-acid change position. Default AA_Position.

protein.change.col

Column name of protein change information (e.g., p.K960R, G658S, L14Sfs*15). Default is a list of Protein_Change, HGVSp_Short.

factor.col

column of classes in the plot legend. IF NA, use parsed Mutation_Class column, otherwise, use specified. Default NA.

plot.options

options of lollipop plot in list format

Examples

# NOT RUN {
# Example 1: visualize mutation data from cBioPortal
#   note: internet access required, may use more than 10 seconds
mutation.dat <- getMutationsFromCbioportal("msk_impact_2017", "TP53")
# lollipop diagram with default options
g3Lollipop(mutation.dat, gene.symbol = "TP53")
# }
# NOT RUN {
# Example 2: visualize mutation data from MAF file
# load MAF file
maf.file <- system.file("extdata", "TCGA.BRCA.varscan.somatic.maf.gz", package = "g3viz")
mutation.dat <- readMAF(maf.file)

# lollipop diagram, classified by "Variant_Classification"
# plot options: add chart title
plot.options <- g3Lollipop.options(
                     chart.margin = list(left = 40, right = 40, top = 30, bottom = 25),
                     title.text = "PIK3CA (TCGA-BRCA)",
                     title.font = "normal 20px Sans",
                     title.color = "steelblue",
                     title.alignment = "middle",
                     title.dy = "0.3em")
g3Lollipop(mutation.dat,
           gene.symbol = "PIK3CA",
           factor.col = "Variant_Classification",
           plot.options = plot.options)

# Example 3: visualize mutation data in CSV or TSV formatted file
# load data
mutation.csv <- system.file("extdata", "ccle.csv", package = "g3viz")

# customized column names
mutation.dat <- readMAF(mutation.csv,
                        gene.symbol.col = "Hugo_Symbol",
                        variant.class.col = "Variant_Classification",
                        protein.change.col = "amino_acid_change",
                        sep = ",")  # separator of csv file

# plot options: try to mimic MutationMapper (http://www.cbioportal.org/mutation_mapper.jsp)
#               change color scheme of mutation track and domain annotation track
plot.options <- g3Lollipop.options(chart.width = 1600,
                                   chart.type = "circle",
                                   lollipop.track.background = "transparent",
                                   lollipop.pop.max.size = 4,
                                   lollipop.pop.min.size = 4,
                                   lollipop.pop.info.limit = 4.1, # same pop size
                                   y.axis.label = "# Mutations",
                                   lollipop.line.color = "grey",
                                   lollipop.line.width = 0.5,
                                   lollipop.circle.color = "black",
                                   lollipop.circle.width = 0.5,
                                   lollipop.color.scheme = "bottlerocket2",
                                   anno.bar.margin = list(top = 5, bottom = 5),
                                   domain.color.scheme = "darjeeling2",
                                   domain.text.font = "normal 8px Arial",
                                   domain.text.color = "white")

g3Lollipop(mutation.dat,
           gene.symbol = "APC",
           protein.change.col = "amino_acid_change",
           plot.options = plot.options)

# }