Repository of the TRanslational ONCOlogy library, which includes various algorithms (such as CAPRESE and CAPRI) and the Pipeline for Cancer Inference (PICNIC).
> maf=read.table("maf.txt",sep = "\t")
> maf1=maf[1:100,]
>maf2=maf[101:296,]
>maf1$Tumor_Sample_Barcode=gsub("test","try",maf1$Tumor_Sample_Barcode)
> maf=rbind(maf1,maf2)
>dataset_maf = import.MAF(maf,merge.mutation.types = FALSE)
*** Importing from dataframe
Loading MAF dataframe ...DONE
*** Mutations names: using Hugo_Symbol
*** Using full MAF: #entries 296
*** MAF report: TCGA=TRUE
Type of annotated mutations:
[1] "Frame_Shift_Del" "Frame_Shift_Ins" "Nonsense_Mutation" "In_Frame_Del" "In_Frame_Ins"
[6] "Unknown"
*** [merge.mutation.types = T] Mutations will be merged and annotated as 'Mutation'
Number of samples: 2
[TCGA = TRUE] Number of TCGA patients: 2
Number of annotated mutations: 296
Mutations annotated with "Valid" flag (%): missing flag
Number of genes (Hugo_Symbol): 181
Starting conversion from MAF to 0/1 mutation profiles (1 = mutation) :2 x 181
........................................................................................................................................................................................................................................................................................................
Starting conversion from MAF to TRONCO data type.
Warning message:
In valid.calls(maf) : Missing Validation_Status flag in MAF file.
> oncoprint(dataset_maf)
*** Oncoprint for ""
with attributes: stage = FALSE, hits = TRUE
Sorting samples ordering to enhance exclusivity patterns.
Setting automatic row font (exponential scaling): 2
>
It seems that you only have 2 samples selected, that do not share mutations among them.
To this end, the oncoprint seems fine.
Let me know if there is anything I am missing.
Hi
I have written my maf file to a txt attached here
maf.txt
I get this plot
Please help me to know where I am doing wrong
Thanks for any help