PapenfussLab / StructuralVariantAnnotation

R package designed to simplify structural variant analysis
GNU General Public License v3.0
68 stars 15 forks source link

Getting this annotation for manta .vcf #17

Closed beginner984 closed 5 years ago

beginner984 commented 5 years ago

Hi,

I have called SV by Manta, how I could get this specific formats for my .vcf files please?

I have attached a sample .vcf and a desired annotation

LP2000104-DNA_A01_vs_LP2000101-DNA_A01.SVannotated.txt

candidateSV.vcf.gz

I have been given a ruby script to convert .vcf to BEDEP then R script to get this annotation but I am very bad in coding

So, I am wondering if I could get this annotation at all

d-cameron commented 5 years ago

If you already have a script to do this, why not just run that script?

I have been given a ruby script to convert .vcf to BEDEP

StructuralVariantAnnotation can do this entirely in R.

vcf = readVcf("candidateSV.vcf.gz`)
bpgr = breakpointRanges(vcf)

R script to get this annotation

bpgr$MobileElement = ""
hits = findOverlaps(bpgr, me_gr, ignore.strand=TRUE)
bpgr$MobileElement [queryHits(hits)] = me_gr[subjectHits(hits)]$mobile_element_annotation

I am very bad in coding

Everyone was bad when the first started. Keep learning :)

beginner984 commented 5 years ago

Sorry to be this much silly

I have been asked to visualize SV data; You please imagine I have a tumor and its matched model (organoid). I have called SV by Manta (my .vcf files are here)

https://www.dropbox.com/s/mhr63rn6v0fx89k/t_005.vcf?dl=0

https://www.dropbox.com/s/80o836njwgnw81k/o_005.vcf?dl=0

How I can get this picture from this paper

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006596

journal pcbi 1006596 g005

Even code for producing this picture is here

https://github.com/DGendoo/PDACDiseaseModels/tree/master/SV/PrimaryPairs

But I don't know how use these scripts to produce such picture of my .vcf files

Could you please help me?

d-cameron commented 5 years ago

As issue does not involve a bug, feature request, or documentation issue with the StructuralVariantAnntoation package, this issues list is not the appropriate location for this question. Whilst I disagree with the approach to SV analysis taken in that paper, I consider that the complexity of analysis and the depth of understand required to produce the figure you have shown sufficient to warrant an authorship position on the paper in question. That said, just blinding reproducing the same figure on different data is more straight-forward but by no means trivial. I recommend you break the figure down into each component and tackle these one at a time, starting with panels A and B.

This question is much better suited to biostars.org or seqanswers.com