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Last data update: 2014.03.03

R: import.MAF

import.MAF

R Documentation

import.MAF

Description

Import mutation profiles from a Manual Annotation Format (MAF) file. All mutations are aggregated as a unique event type labeled "Mutation" and assigned a color according to the default of function import.genotypes. If this is a TCGA MAF file check for multiple samples per patient is performed and a warning is raised if these occurr. Customized MAF files can be imported as well provided that they have columns Hugo_Symbol, Tumor_Sample_Barcode and Variant_Classification. Custom filters are possible (via filter.fun) to avoid loading the full MAF data

Usage

import.MAF(file, sep = "\t", is.TCGA = TRUE, filter.fun = NULL,
  to.TRONCO = TRUE, irregular = FALSE, paste.to.Hugo_Symbol = NULL,
  merge.mutation.types = TRUE, silent = FALSE)

Arguments

`file`	MAF filename
`sep`	MAF separator, default '\t'
`is.TCGA`	TRUE if this MAF is from TCGA; thus its sample codenames can be interpreted
`filter.fun`	A filter function applied to each row. This is expected to return TRUE/FALSE.
`to.TRONCO`	If FALSE returns a dataframe with MAF data, not a TRONCO object
`irregular`	If TRUE seeks only for columns Hugo_Symbol, Tumor_Sample_Barcode and Variant_Classification
`paste.to.Hugo_Symbol`	If a list of column names, this will be pasted each Hugo_Symbol to yield names such as PHC2.chr1.33116215.33116215
`merge.mutation.types`	If TRUE, all mutations are considered equivalent, regardless of their Variant_Classification value. Otherwise no.
`silent`	A parameter to disable/enable verbose messages.

Value

A TRONCO compliant representation of the input MAF

Examples

data(maf)
mutations = import.MAF(maf)
mutations = annotate.description(mutations, 'Example MAF')
mutations = TCGA.shorten.barcodes(mutations)
oncoprint(mutations)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(TRONCO)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/TRONCO/import.MAF.Rd_%03d_medium.png", width=480, height=480)
> ### Name: import.MAF
> ### Title: import.MAF
> ### Aliases: import.MAF
> 
> ### ** Examples
> 
> data(maf)
> mutations = import.MAF(maf)
*** Importing from dataframe
Loading MAF dataframe ...DONE
*** Mutations names: using Hugo_Symbol
*** Using full MAF: #entries  16 
*** MAF report: TCGA=TRUE
Type of annotated mutations: 
[1] Missense_Mutation Silent            Nonsense_Mutation Frame_Shift_Ins  
Levels: Frame_Shift_Ins Missense_Mutation Nonsense_Mutation Silent
*** [merge.mutation.types = T] Mutations will be merged and annotated as 'Mutation'
Number of samples: 3 
[TCGA = TRUE] Number of TCGA patients: 3 
Number of annotated mutations: 16 
Mutations annotated with "Valid" flag (%): 88 
Number of genes (Hugo_Symbol): 13 
Starting conversion from MAF to 0/1 mutation profiles (1 = mutation) :3 x 13 
................
Starting conversion from MAF to TRONCO data type.
> mutations = annotate.description(mutations, 'Example MAF')
> mutations = TCGA.shorten.barcodes(mutations)
> oncoprint(mutations)
*** Oncoprint for "Example MAF"
with attributes: stage = FALSE, hits = TRUE
Sorting samples ordering to enhance exclusivity patterns.
Setting automatic row font (exponential scaling): 11.6
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>