compTMB: Comparsion of total mutation burden
In xlucpu/MOVICS: Multi-Omics integration and VIsualization in Cancer Subtyping

Description Usage Arguments Value References Examples

This function calculates Total Mutation Burden (TMB) compares them among curent subtypes identified from multi-omics integrative clustering algorithms.

compTMB(
  moic.res = NULL,
  maf = NULL,
  rmDup = TRUE,
  rmFLAGS = FALSE,
  nonSyn = NULL,
  exome.size = 38,
  clust.col = c("#2EC4B6", "#E71D36", "#FF9F1C", "#BDD5EA", "#FFA5AB", "#011627",
    "#023E8A", "#9D4EDD"),
  test.method = "nonparametric",
  show.size = TRUE,
  fig.path = getwd(),
  fig.name = NULL,
  width = 6,
  height = 6
)

`moic.res`	An object returned by 'getMOIC()' with one specified algorithm or 'get%algorithm_name%' or 'getConsensusMOIC()' with a list of multiple algorithms.
`maf`	A data frame of MAF file that has been already read with at least 10 columns as following: c('Tumor_Sample_Barcode', 'Hugo_Symbol', 'Chromosome', 'Start_Position', 'End_Position', 'Variant_Classification', 'Variant_Type', 'Reference_Allele', 'Tumor_Seq_Allele1', 'Tumor_Seq_Allele2')
`rmDup`	A logical value to indicate if removing repeated variants in a particuar sample, mapped to multiple transcripts of same Gene. TRUE by default.
`rmFLAGS`	A logical value to indicate if removing possible FLAGS. These FLAGS genes are often non-pathogenic and passengers, but are frequently mutated in most of the public exome studies, some of which are fishy. Examples of such genes include TTN, MUC16, etc. FALSE by default.
`nonSyn`	A string vector to indicate a list of variant claccifications that should be considered as non-synonymous and the rest will be considered synonymous (silent) variants. Default value of NULL uses Variant Classifications with High/Moderate variant consequences, including c('Frame_Shift_Del', 'Frame_Shift_Ins', 'Splice_Site', 'Translation_Start_Site', 'Nonsense_Mutation', 'Nonstop_Mutation', 'In_Frame_Del', 'In_Frame_Ins', 'Missense_Mutation'). See details at http://asia.ensembl.org/Help/Glossary?id=535
`exome.size`	An integer value to indicate the estimation of exome size. 38 by default (see https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-017-0424-2).
`clust.col`	A string vector storing colors for annotating each Subtype.
`test.method`	A string value to indicate the method for statistical testing. Allowed values contain c('nonparametric', 'parametric'); nonparametric means two-sample wilcoxon rank sum test for two subtypes and Kruskal-Wallis rank sum test for multiple subtypes; parametric means two-sample t-test when only two subtypes are identified, and anova for multiple subtypes comparison; "nonparametric" by default.
`show.size`	A logical value to indicate if showing the sample size within each subtype at the top of the figure. TRUE by default.
`fig.path`	A string value to indicate the output path for storing the boxviolin plot.
`fig.name`	A string value to indicate the name of the boxviolin plot.
`width`	A numeric value to indicate the width of boxviolin plot.
`height`	A numeric value to indicate the height of boxviolin plot.

A figure of TMB and TiTv distribution (.pdf) and a list with the following components:

TMB.dat a data.frame storing the TMB per sample within each subtype.

TMB.median a data.frame storing the median of TMB for each subtype.

titv.dat a data.frame storing the fraction contributions of TiTv per sample within each subtype.

maf.nonsilent a data.frame storing the information for non-synonymous mutations.

maf.silent a data.frame storing the information for synonymous mutations.

maf.FLAGS a data.frame storing the information for FLAGS mutations ifrmFLAGS = TRUE.

FLAGS.count a data.frame storing the summarization per FLAGS ifrmFLAGS = TRUE.

Mayakonda A, Lin D, Assenov Y, Plass C, Koeffler PH (2018). Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res, 28(11): 1747-1756.

Shyr C, Tarailo-Graovac M, Gottlieb M, Lee JJ, van Karnebeek C, Wasserman WW. (2014). FLAGS, frequently mutated genes in public exomes. BMC Med Genomics, 7(1): 1-14.

Chalmers Z R, Connelly C F, Fabrizio D, et al. (2017). Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med, 9(1):34.