prettyForestPlot.RdCreate a forest plot comparing mutation frequencies for a set of genes between two groups.
prettyForestPlot(
maf,
mutmat,
metadata,
genes,
min_mutations = 1,
comparison_column,
rm_na_samples = FALSE,
comparison_values = FALSE,
separate_hotspots = FALSE,
comparison_name = FALSE,
custom_colours = FALSE,
custom_labels = FALSE,
max_q = 1
)A maf data frame. Minimum required columns are Hugo_Symbol and Tumor_Sample_Barcode.
Optional argument for binary mutation matrix. If not supplied, function will generate this matrix from the file used in argument "maf".
Metadata for the comparisons. Minimum required columns are Tumor_Sample_Barcode and the column assigning each case to one of two groups.
An optional vector of genes to restrict your plot to. If no gene-list is supplied, the function will extract all mutated genes from the incoming maf. See min_mutations parameter for more info.
Optional parameter for when no genes is provided. This parameter ensures only genes with n mutations are kept in genes. Default value is 1, this means all genes in the incoming maf will be plotted.
Mandatory: the name of the metadata column containing the comparison values.
Set to TRUE to remove 0 mutation samples. Default is FALSE.
Optional: If the comparison column contains more than two values or is not a factor, specify a character vector of length two in the order you would like the factor levels to be set, reference group first.
Optional: If you would like to treat hotspots separately from other mutations in any gene. Requires that the maf file is annotated with annotate_hotspots.
Optional: Specify the legend title if different from the comparison column name.
Optional: Specify a named vector of colours that match the values in the comparison column.
Optional: Specify custom labels for the legend categories. Must be in the same order as comparison_values.
cut off for q values to be filtered in fish test
A convenient list containing all the data frames that were created in making the plot, including the mutation matrix. It also produces (and returns) ggplot object with a side-by-side forest plot and bar plot showing mutation incidences across two groups.
This function returns two types of plot (box plot and forest plot), the user can either view them separately or arranged on the same grob.
In addition this function also lets the user control the mutation frequencies of the plotted genes.
If no genes is provided, this function auto-defaults to all genes in the incoming maf.
The user can then control the minimum number of mutations requirement for a gene to be included in the plot.
This is done with the min_mutations parameter.
For extended examples on how to use this function, refer to the example inside the function documentation or the vignettes.
metadata = get_gambl_metadata(case_set = "tFL-study")
#> Joining with `by = join_by(sample_id)`
#> Joining with `by = join_by(sample_id)`
this_meta = dplyr::filter(metadata, pairing_status == "matched")
this_meta = dplyr::filter(this_meta, consensus_pathology %in% c("FL", "DLBCL"))
maf = get_coding_ssm(limit_samples = this_metadata$sample_id,
basic_columns = TRUE,
seq_type = "genome")
#> Error in dplyr::filter(., sample_id %in% limit_samples): ℹ In argument: `sample_id %in% limit_samples`.
#> Caused by error in `h()`:
#> ! error in evaluating the argument 'table' in selecting a method for function '%in%': object 'this_metadata' not found
prettyForestPlot(maf = maf,
metadata = this_metadata,
genes = c("ATP6V1B2",
"EZH2",
"TNFRSF14",
"RRAGC"),
comparison_column = "consensus_pathology",
comparison_values = c("DLBCL",
"FL"),
separate_hotspots = FALSE,
comparison_name = "FL vs DLBCL")
#> Error in prettyForestPlot(maf = maf, metadata = this_metadata, genes = c("ATP6V1B2", "EZH2", "TNFRSF14", "RRAGC"), comparison_column = "consensus_pathology", comparison_values = c("DLBCL", "FL"), separate_hotspots = FALSE, comparison_name = "FL vs DLBCL"): object 'this_metadata' not found