All functions

CNregions.mod()

CNregions.mod Modified CNregions function from the facets package to handle small sample sizes.

add.perc()

Add a percentage to counts

binmat()

binmat \ Enables creation of a binary matrix from a maf file with a predefined list of patients (rows are patients and columns are genes)

check_maf_column()

Check Columns of MAF

check_maf_input()

Checks MAF input to ensure column names are correct and renamed genes are corrected

clin.patients

An example of clinical patient level information file from IMPACT cbioPortal dataset.

clin.sample

An example of clinical sample level information file from IMPACT cbioPortal dataset.

cna

An example copy number alteration raw calls file from IMPACT cbioPortal dataset

curated_genes

List of curated genes for IMPACT oncoKB annotation.

custom_pathway()

custom_pathway \ Enables creation of a custom pathway binary matrix from a binmat() object. Similarly to the internal file 'pathways.csv', this function takes as input a data frame containing the name of the pathways of interest, and for each pathways a character vector of the genes of interest. Note that the different events to be considered in each pathways must be considered separetely. For example, if one wishes to consider TP53 deletions in a given pathway, one must specify "TP53.Del" in the character vector for that pathway.

dat.oncoPrint()

dat.oncoPrint Enables creation of a matrix used to generate an OncoPrint heatmap.

facets.dat()

facets.dat

facets.heatmap()

facets.heatmap

fusion

An example of fusions calls file from IMPACT cbioPortal dataset

gen.summary()

gen.summary

get_tmb()

get_tmb \ Function to calculate the tumor mutation burden of individual patients in a MAF file. Note that this can only be applied to samples sequenced using one of the IMPACT panels. Other samples will be annotated as missing.

ggcomut()

Co-mutation Heatmap of the Top Altered Genes

gggenecor()

Correlation Heatmap of the Top Altered Genes

ggheatmap()

Heatmap of all events after binmat - using binary distance

ggsamplevar()

Histogram of Variants Per Sample Colored By Variant Classification

ggsnvclass()

Histogram of SNV class Counts

ggtopgenes()

Barplot of Most Frequently Altered Genes

ggvarclass()

Barplot of Variant Classification Counts

ggvartype()

Barplot of Variant Type Counts

gnomer_colors

List of suggested color palettes for when you need a large palette

gnomer_cols()

Function to extract colors from gnomer_colors as hex codes

gnomer_pal()

Return function to interpolate a gnomeR color palette

gnomer_palette()

Access the colors in a gnomeR color palette

gnomer_palettes

Complete list of gnomeR color palettes

impact_gene_info

IMPACT Gene Meta Data

maf_viz()

Creates a set of plot summarising a maf file.

mut

An example maf file from IMPACT cbioPortal dataset

oncokb()

OncoKB annotate \ Enables oncokb annotation of MAF, fusions and CNA files. This is performed using the OncoKB annotator found at https://github.com/oncokb/oncokb-annotator. See details there for file formats.

pathways

IMPACT Gene Pathways

plot_oncoPrint()

plot_oncoPrint Creates the OncoPrint corresponding to the inputted genetic data

resolve_alias()

Resolve Hugo Symbol Names with Aliases

scale_color_pancan()

Color scale creator to add gnomeR colors in ggplot

scale_fill_pancan()

Fill scale creator to add gnomeR colors in ggplot

seg

A segmentation file from the cbioPortal datasets

substrRight()

Utility Function to Extract SNV

tcga_genes

A vector of 19441 hugo symbols in TCGA

tcga_samples

Data frame of all TCGA sample ids and their corresponding cancer type

ti_341

Intervals sequenced in 341 panel

ti_410

Intervals sequenced in 410 panel

ti_468

Intervals sequenced in 468 panel

uni.cox()

uni.cox Performs univariate cox proportional hazard model on every feature