[BioC] Complete variant toolbox: gmapR/VariantTools/VariantAnnotation

[Thomas Girke]

Thanks Wei for pointing this out, and sorry for missing this important
utility. I will definitely give your exactSNP function a try. Associating 
Rsubread with the biocViews term "GeneticVariability" (or similar) would 
help users finding it in the future.

Thanks,

Thomas

On Mon, Dec 09, 2013 at 02:12:23AM +0000, Wei Shi wrote:
> I just want to point out that Rsubread package includes a snp calling function called exactSNP.
> 
> Wei
> 
> On Dec 9, 2013, at 4:08 AM, Thomas Girke wrote:
> 
> > Dear Michael and Valerie,
> > 
> > VariantTools and VariantAnnotation are awesome packages. To the best of my
> > knowledge, VariantTools is currently the only Bioc/R package that performs
> > variant calling and it does this in a very nice way. With the available
> > resources it is now straightforward to set up complete workflows for variant
> > calling projects: (1) variant aware read alignments with GSNAP from gmapR ->
> > (2) variant calling/filtering with VariantTools -> (3) adding genomic context
> > with VariantAnnotation. This is really amazing!!! 
> > 
> > Here are a few questions related to both packages:
> > 
> > (1) For teaching purposes and other obvious reasons it would be useful if a
> > Windows version of VariantTools were available (and perhaps for gmapR too).
> > Installing the package (includes gmapR) from source works fine on both Linux
> > and OS X, but not on Windows. 
> > 
> > (2) The VRanges class is another great resource for filtering variant calls.
> > What I was not able to locate though is a description/definition of the content
> > of its different columns/components. Is something like this available
> > somewhere? 
> > 
> > (3) When annotation variants with utilities from VariantAnnotation, it would
> > useful to provide a convenience Summary Report function at the end of the
> > workflow that exports the annotations to a file. A very common need here is to
> > collapse the annotations for each variant on a single line so that one doesn't
> > end up with annotation results of millions of lines as it is typical for many
> > variant discovery projects. This also simplifies joins among different
> > annotation instances because it maintains uniqueness among variant identifiers.
> > This approach is often useful when comparing (joining) the variants among
> > different genotypes (e.g. which variants are identical or unique among
> > different mutants). An example solution is shown on slides 34-35 of this
> > presentation:
> > http://faculty.ucr.edu/~tgirke/HTML_Presentations/Manuals/Workshop_Dec_12_16_2013/Rvarseq/Rvarseq.pdf
> > 
> > (4) predictCoding() reports the relative location where exactly a variant maps
> > to an annotation range. It would be nice if locateVariants() could report the
> > exact relative mapping locations too, e.g. variant chr1:1033_A/T maps to
> > position x of 5'UTR. Perhaps this is already possible but I couldn't figure
> > out how to do it without reaching too far into my own hacking toolbox.
> > 
> > Thanks for providing these excellent resources and most importantly your patience 
> > listing to these unsolicited questions.
> > 
> > Best,
> > 
> > 
> > Thomas
> > 
> > 
> > 
> >> sessionInfo()
> > R version 3.0.2 (2013-09-25)
> > Platform: x86_64-apple-darwin10.8.0 (64-bit)
> > 
> > locale:
> > [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
> > 
> > attached base packages:
> > [1] parallel  stats     graphics  grDevices utils     datasets  methods
> > [8] base
> > 
> > other attached packages:
> > [1] VariantTools_1.4.5      VariantAnnotation_1.8.7 Rsamtools_1.14.2
> > [4] Biostrings_2.30.1       GenomicRanges_1.14.3    XVector_0.2.0
> > [7] IRanges_1.20.6          BiocGenerics_0.8.0
> > 
> > loaded via a namespace (and not attached):
> > [1] AnnotationDbi_1.24.0   BatchJobs_1.1-1135     BBmisc_1.4
> > [4] Biobase_2.22.0         BiocParallel_0.4.1     biomaRt_2.18.0
> > [7] bitops_1.0-6           brew_1.0-6             BSgenome_1.30.0
> > [10] codetools_0.2-8        DBI_0.2-7              digest_0.6.3
> > [13] fail_1.2               foreach_1.4.1          GenomicFeatures_1.14.2
> > [16] gmapR_1.4.2            grid_3.0.2             iterators_1.0.6
> > [19] lattice_0.20-24        Matrix_1.1-0           plyr_1.8
> > [22] RCurl_1.95-4.1         RSQLite_0.11.4         rtracklayer_1.22.0
> > [25] sendmailR_1.1-2        stats4_3.0.2           tools_3.0.2
> > [28] XML_3.95-0.2           zlibbioc_1.8.0
> > 
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