tcgaCompare | R Documentation |
Compares mutation load in input MAF against all of 33 TCGA cohorts derived from MC3 project.
tcgaCompare(
maf,
capture_size = NULL,
tcga_capture_size = 35.8,
cohortName = NULL,
tcga_cohorts = NULL,
primarySite = FALSE,
col = c("gray70", "black"),
bg_col = c("#EDF8B1", "#2C7FB8"),
medianCol = "red",
decreasing = FALSE,
logscale = TRUE,
rm_hyper = FALSE,
rm_zero = TRUE,
cohortFontSize = 0.8,
axisFontSize = 0.8
)
maf |
|
capture_size |
capture size for input MAF in MBs. Default NULL. If provided plot will be scaled to mutations per mb. TCGA capture size is assumed to be 35.8 mb. |
tcga_capture_size |
capture size for TCGA cohort in MB. Default 35.8. Do NOT change. See details for more information. |
cohortName |
name for the input MAF cohort. Default "Input" |
tcga_cohorts |
restrict tcga data to these cohorts. |
primarySite |
If TRUE uses primary site of cancer as labels instead of TCGA project IDs. Default FALSE. |
col |
color vector for length 2 TCGA cohorts and input MAF cohort. Default gray70 and black. |
bg_col |
background color. Default'#EDF8B1', '#2C7FB8' |
medianCol |
color for median line. Default red. |
decreasing |
Default FALSE. Cohorts are arranged in increasing mutation burden. |
logscale |
Default TRUE |
rm_hyper |
Remove hyper mutated samples (outliers)? Default FALSE |
rm_zero |
Remove samples with zero mutations? Default TRUE |
cohortFontSize |
Default 0.8 |
axisFontSize |
Default 0.8 |
Tumor mutation burden for TCGA cohorts is obtained from TCGA MC3 study. For consistency TMB is estimated by restricting variants within Agilent Sureselect capture kit of size 35.8 MB.
data.table with median mutations per cohort
TCGA MC3 file was obtained from https://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc. See TCGAmutations R package for more details. Further downstream script to estimate TMB for each sample can be found in ‘inst/scripts/estimate_tcga_tmb.R’
Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines Kyle Ellrott, Matthew H. Bailey, Gordon Saksena, et. al. Cell Syst. 2018 Mar 28; 6(3): 271–281.e7. https://doi.org/10.1016/j.cels.2018.03.002
laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
laml <- read.maf(maf = laml.maf)
tcgaCompare(maf = laml, cohortName = "AML")
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