Question: Estimating Ld Blocks
gravatar for Hanif Khalak
8.8 years ago by
Hanif Khalak1.2k
Doha, QA
Hanif Khalak1.2k wrote:

I'm trying to get a handle on how LD patterns define blocks which are often interpreted as haplotype boundaries. I have LD data (D', r^2) and would like to come up with or use an existing function which takes this matrix and can generate row IDs for the boundaries of each "block".

Is there a BioConductor package or other tool which does this, or a paper which describes a simple approach I could try? The matrix looks "block-diagonal" so I imagine even a technique from linear algebra might have a simple procedure, e.g. this Matlab function (which I don't have access to)?

linkage haplotype • 5.2k views
ADD COMMENTlink modified 4.4 years ago by Biostar ♦♦ 20 • written 8.8 years ago by Hanif Khalak1.2k
gravatar for Khader Shameer
8.8 years ago by
Manhattan, NY
Khader Shameer18k wrote:

If you are can think out of R, you can try using PLINK (See section on LD calculations) or Haploview (See Haploview tutorial here) for estimation / visualization of LD blocks. I would like to recommend PLINK, it can be easily integrated in to your work-flows, but Haploview is more of a GUI based. If you are too specific on R, there is an R plug-in for PLINK too.

ADD COMMENTlink written 8.8 years ago by Khader Shameer18k

Thanks for the [p]link - I was hoping for something that I could use with the LD matrix and wouldn't require the raw genotypes

ADD REPLYlink written 8.8 years ago by Hanif Khalak1.2k
gravatar for Laurent Gautier
8.7 years ago by
Laurent Gautier810 wrote:

LDheatmap (although on CRAN, not on Bioconductor) will help with making a visualization of your LD data. The function retuns (invisibly) an object with details for the plot that you could use.

For dealing with almost-block matrices, the packges limSolve might have utilities.

ADD COMMENTlink written 8.7 years ago by Laurent Gautier810
gravatar for Larry_Parnell
8.7 years ago by
Boston, MA USA
Larry_Parnell16k wrote:

We do a lot of this in our group and I mean a lot. Our choices are HelixTree (GoldenHelix) and TAGGER/Haploview (Haploview employs TAGGER). I have heard a lot of talk about PLINK. Our collaborators with the GOLDN study use it. We find HelixTree to be more robust.

ADD COMMENTlink modified 8.7 years ago • written 8.7 years ago by Larry_Parnell16k
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