visualizing mutational data using Maftools for reference genome hg19

Dear all,

I am trying to do somatic variation analysis using TCGABiolinks package in R 3.6.

I want to use hg19 version of human genome. However I could not find any way to visualize the results using Maftools. It seems Maftools has only been designed for hg38.

The following is the punch of codes I used for data visualization by Maftools:

 library(maftools)
    library(dplyr)

    maf <- GDCquery_Maf("KIRP", pipelines = "mutect") %>% read.maf

    datatable(getSampleSummary(maf),
              filter = 'top',
              options = list(scrollX = TRUE, keys = TRUE, pageLength = 5000), 
              rownames = FALSE)

    plotmafSummary(maf = maf, rmOutlier = TRUE, addStat = 'median', dashboard = TRUE)

    oncoplot(maf = maf, top = 20, removeNonMutated = TRUE)
    titv = titv(maf = maf, plot = FALSE, useSyn = FALSE)
    #plot titv summary
    plotTiTv(res = titv)

Can you guide me how to change this code to be used for hg19?

I am looking forward to your comments

Nazanin

hg19 visualize maftools snv

• 2,457 views • link

written 5.9 years ago by nazaninhoseinkhan

Default in maftools is hg19 unless you change that

Only gisticChromPlot uses chromosome length information for plotting. Default is hg19 and can be changed with ref.build argument.

• 0 views • link

written 5.9 years ago by zizigolu

Hi, After running "maf <- GDCquery_Maf("CESC", pipelines = "mutect") %>% read.maf", I get this :

-------------------------------------
o GDCquery: Searching in GDC database
--------------------------------------
Genome of reference: hg38
--------------------------------------------
oo Accessing GDC. This might take a while...
--------------------------------------------
ooo Project: TCGA-CESC
--------------------
oo Filtering results
--------------------
ooo By access
ooo By data.type
ooo By workflow.type
----------------
oo Checking data
----------------
ooo Check if there are duplicated cases
ooo Check if there results for the query
-------------------
o Preparing output
-------------------

In line 2 you can see the version of genome reference is hg38

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written 5.9 years ago by nazaninhoseinkhan

Actually you don't need this

I suggest you may just download maf file for cancer of your interest here

enter image description here

You then use merge_maf function from Maftools itself to read what you have downloaded (click on the mutation annotation ) the files name is gdac.broadinstitute.org_CESC.Mutation_Packager_Oncotated_Calls.Level_3.2016012800.0.0

Default in maftoools is hg19

• 0 views • link

written 5.9 years ago by zizigolu

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