copy number variation analysis (CNV)
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sijing.gsj • 0
Last seen 8 months ago

Hi, I’m running a project concerning copy number variation analysis. To run the analysis, I need to visualize the copy number data that I have. The data I have is in VCF files:

##source=CNVkit v0.9.1.dev0                             
##INFO=<ID=CIEND,Number=2,Type=Integer,Description="Confidence interval around END for imprecise variants">                             
##INFO=<ID=CIPOS,Number=2,Type=Integer,Description="Confidence interval around POS for imprecise variants">                             
##INFO=<ID=END,Number=1,Type=Integer,Description="End position of the variant described in this record">        
#CHROM  POS ID  REF ALT QUAL    FILTER  INFO    FORMAT  I92489 chr8 32614538    .   N   <DEL>   .   .   IMPRECISE;SVTYPE=DEL;END=41932272;SVLEN=-9317734;FOLD_CHANGE=0.680550;FOLD_CHANGE_LOG=-0.555227;PROBES=347  GT:GQ:CN:DP 0/1:347:0:889.61 chr19  8868368 .   N   <DEL>   .   .   IMPRECISE;SVTYPE=DEL;END=8922807;SVLEN=-54439;FOLD_CHANGE=0.697826;FOLD_CHANGE_LOG=-0.519061;PROBES=162 GT:GQ:CN:DP 0/1:162:0:783.79 chr21  6486300 .   N   <DEL>   .   .   IMPRECISE;SVTYPE=DEL;END=6499298;SVLEN=-12998;FOLD_CHANGE=0.305717;FOLD_CHANGE_LOG=-1.709730;PROBES=10  GT:GQ:CN:DP 1/1:10:0:304.14

Is there a R package that can help transform this kind of data into a plot where you can visualize the copy number of genes in the chromosome?

Any kind of help is greatly appreciated!example in a publication

copynumber plot visualization NGS gene • 261 views
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Please use the formatting bar (especially the code option) to present your post better. You can use backticks for inline code (inline formatting looks like this: text), or select a chunk of text and use the highlighted button to format it as a code block.

That would look like this:

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As a first step, the VariantAnnotation package can be use to input VCF files...

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Last seen 6 months ago

Just doing a quick Google search, I found this:

2.4 Visualization
Several tools are available in the package for the plotting of data and segmentation results. These
include plotGenome, plotSample, and plotChrom where data and/or segments are plotted over
the entire genome, for a given sample across different chromosomes and for a given chromosome
across different samples, respectively. Other graphical tools include plotHeatmap, which plots copy
numbers heatmaps, and plotFreq, which plots the frequency of samples with an aberration at a
genomic position. In addition, plotCircle enables the plotting of the genome as a circle with
aberration frequencies and connections between genomic loci added to the middle of the circle.

I'm guessing you could input your VCF using your preferred method and then somehow convert it into a dataframe compatible with the function in question. From plotChrom()(pdf):

data: a data frame with numeric or character chromosome numbers in the first column,
numeric local probe positions in the second, and numeric copy number data for
one or more samples in subsequent columns. The header of the copy number
columns should be the sample IDs.

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