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 |