Get Coding SSM Status.
get_coding_ssm_status.RdTabulate mutation status (SSM) for a set of genes.
Usage
get_coding_ssm_status(
gene_symbols,
these_samples_metadata,
maf_data,
include_hotspots = TRUE,
keep_multihit_hotspot = FALSE,
review_hotspots = TRUE,
genes_of_interest = c("FOXO1", "MYD88", "CREBBP"),
genome_build,
include_silent = FALSE,
include_silent_genes,
...
)Arguments
- gene_symbols
A vector of gene symbols for which the mutation status will be tabulated. If not provided, lymphoma genes will be returned by default.
- these_samples_metadata
The metadata for samples of interest to be included in the returned matrix. Only the column "sample_id" is required. If not provided, the example metadata is used as default.
- maf_data
data frame in maf format. Must be in the grch37 projection.
- include_hotspots
Logical parameter indicating whether hotspots object should also be tabulated. Default is TRUE.
- keep_multihit_hotspot
Logical parameter indicating whether to keep the gene annotation as mutated when the gene has both hot spot and non-hotspot mutation. Default is FALSE. If set to TRUE, will report the number of non-hotspot mutations instead of tabulating for just mutation presence.
- review_hotspots
Logical parameter indicating whether hotspots object should be reviewed to include functionally relevant mutations or rare lymphoma-related genes. Default is TRUE.
- genes_of_interest
A vector of genes for hotspot review. Currently only FOXO1, MYD88, and CREBBP are supported.
- genome_build
Reference genome build for the coordinates in the MAF file. The default is inferred from maf_data.
- include_silent
Logical parameter indicating whether to include silent mutations into coding mutations. Default is FALSE.
- include_silent_genes
Optionally, provide a list of genes for which the Silent variants to be considered. If provided, the Silent variants for these genes will be included regardless of the include_silent argument.
- ...
Any other parameter. These parameters will be ignored.
Details
This function takes a data frame (in MAF-like format) and converts it to a binary one-hot encoded matrix of mutation status for either a set of user-specified genes (via gene_symbols) or, if no genes are provided, default to all lymphoma genes. The default behaviour is to assign each gene/sample_id combination as mutated only if there is a protein coding mutation for that sample in the MAF but this can be configured to use synonymous variants in some (via include_silent_genes) or all (via include_silent) genes. This function also has other filtering and convenience parameters giving the user full control of the return. For more information, refer to the parameter descriptions and examples. Currently only the grch37 genome build is supported for hotspot annotation and review for this version of the function.
Examples
coding_tabulated_df = get_coding_ssm_status(
maf_data = get_coding_ssm(),
gene_symbols = c("EZH2","KMT2D","CREBBP","MYC")
)
#> Using the bundled SSM calls (.maf) calls in GAMBLR.data...
#> Using the bundled metadata in GAMBLR.data...
#> after linking with metadata, we have mutations from 817 samples
#> Using the bundled metadata in GAMBLR.data...
#> Joining with `by = join_by(sample_id)`
#> annotating hotspots
#> Joining with `by = join_by(sample_id)`
#> CREBBPHOTSPOT
#> OK
#> MYD88HOTSPOT
#> FOXO1HOTSPOT
head(coding_tabulated_df)
#> sample_id KMT2D CREBBP EZH2 MYC CREBBPHOTSPOT MYD88HOTSPOT
#> 1 Akata 0 0 0 1 0 0
#> 2 BL2 0 0 0 1 0 1
#> 3 BL30 1 0 0 1 0 0
#> 4 BL41 0 0 0 1 0 0
#> 5 BL70 0 0 0 1 0 0
#> 6 BLGSP-71-06-00001-01A-11D 0 0 0 0 0 0
#> FOXO1HOTSPOT
#> 1 1
#> 2 1
#> 3 0
#> 4 0
#> 5 0
#> 6 1
#all lymphoma genes from bundled NHL gene list
coding_tabulated_df = get_coding_ssm_status(
maf_data = get_coding_ssm()
)
#> Using the bundled SSM calls (.maf) calls in GAMBLR.data...
#> Using the bundled metadata in GAMBLR.data...
#> after linking with metadata, we have mutations from 817 samples
#> No gene_symbols provided, defaulting to all lymphoma genes.
#> Using the bundled metadata in GAMBLR.data...
#> Joining with `by = join_by(sample_id)`
#> annotating hotspots
#> Joining with `by = join_by(sample_id)`
#> CREBBPHOTSPOT
#> OK
#> MYD88HOTSPOT
#> OK
#> FOXO1HOTSPOT
#> OK
head(coding_tabulated_df[,c(1:10)])
#> sample_id TNFRSF14 SPEN CARD11 KMT2D BCL7A FOXO1 BCL2 BTK
#> 1 Akata 0 1 0 0 0 0 0 0
#> 2 BL2 0 0 0 0 0 0 0 0
#> 3 BL30 0 0 0 1 0 0 0 0
#> 4 BL41 0 0 0 0 0 0 0 0
#> 5 BL70 0 0 0 0 0 0 0 0
#> 6 BLGSP-71-06-00001-01A-11D 0 0 0 0 0 0 0 0
#> CREBBP
#> 1 0
#> 2 0
#> 3 0
#> 4 0
#> 5 0
#> 6 0
if (FALSE) { # \dontrun{
#this example would fail because hg38 is not supported by this function (yet)
coding_tabulated_df = get_coding_ssm_status(maf_data=
get_coding_ssm(projection = "hg38"))
# Error in get_coding_ssm_status(maf_data = get_coding_ssm(projection = "hg38")) :
# Currently only grch37 projection (hg19 genome build) is supported.
} # }