Tool: ctDNAtools: an R package to work with ctDNA sequencing data
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gravatar for amjad
8 months ago by
amjad90
Finland
amjad90 wrote:

Dear community,

I am pleased to share with you the R package I have developed for analysis of ctDNA sequencing data (ctDNAtools).

https://github.com/alkodsi/ctDNAtools

You can do two kinds of analyses with ctDNAtools:

  1. Minimal residual disease testing: this is useful if you have a list of pre-detected mutations in the tumor (for example detected at diagnosis), and you want to test a follow-up sample whether it has cancer (i.e. ctDNA) or not.
  2. Analysis of cell-free DNA fragmentation: you can study the fragment size histograms, profiles and fragmentation patterns along the genome.

The ctDNAtools package is mainly built on GenomicAlignments and Rsamtools packages, and most functions require inputs including one or more of a bam file, mutations data frame, targets data frame and a reference genome.

You can check the full documentation and the examples in the vignette, and I am happy to answer questions about the usage.

ADD COMMENTlink modified 7 months ago • written 8 months ago by amjad90

For more details check the manuscript in BioRxiv:

https://www.biorxiv.org/content/10.1101/2020.01.27.912790v1

ADD REPLYlink written 7 months ago by amjad90
0
gravatar for amjad
7 months ago by
amjad90
Finland
amjad90 wrote:

For more details check the manuscript in BioRxiv:

https://www.biorxiv.org/content/10.1101/2020.01.27.912790v1

ADD COMMENTlink written 7 months ago by amjad90

Thanks for your tools. I wonder after this step: test3 <- test_ctDNA(mutations = mutations, bam = bamT1, reference = BSgenome.Hsapiens.UCSC.hg19, targets = targets, informative_reads_threshold = 100, black_list = black_list1, substitution_specific = FALSE)

How can I get the vcf file with the dropped mutation or the dropped mutation file. The test3 only tells me how many mutations are dropped but I don't know how to examine the details. thanks.

ADD REPLYlink written 7 months ago by Peter Chung120

Hi Peter, you are right that the output should list these mutations (which could be a future feature). For now you can just run: filter_mutations(mutations, black_list = black_list1, substitution_specific = FALSE)

It will output a dataframe with the left mutations after filtering.

ADD REPLYlink written 7 months ago by amjad90
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