Getting loadings from PCoA

[nmshahir]

Hello,

I am a doctoral student working on a microbiomes project and did an principal coordinates analysis in Phyloseq. While I recognize that PCA and PCoA are not exactly the same, I was wondering if there was a way to get the loadings of the PCoA (i.e. determine how much taxa A, taxa B, etc contribute to PC1, and so forth)?

Code Example:
ord.wuni <- ordinate(data,"PCoA","wunifrac")
PCoA.wuni = plot_ordination(data, ord.wuni, type = "samples", color = "Phenotype")
PCoA.wuni

Thanks in advance for any comments,
Nur

[spholmes]

The reason we use DPCoA instead of wuf is because it provides biplots with
species
loadings that PCoA on wuf doesn't.

On Tue, Aug 16, 2016 at 11:22 AM, nmshahir [email protected] wrote:

Hello,

I am a doctoral student working on a microbiomes project and did an
principal coordinates analysis in Phyloseq. While I recognize that PCA and
PCoA are not exactly the same, I was wondering if there was a way to get
the loadings of the PCoA (i.e. determine how much taxa A, taxa B, etc
contribute to PC1, and so forth)?

Code Example:
ord.wuni <- ordinate(data,"PCoA","wunifrac")
PCoA.wuni = plot_ordination(data, ord.wuni, type = "samples", color =
"Phenotype")
PCoA.wuni

Thanks in advance for any comments,
Nur

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[nmshahir]

I'm going through the documentation (https://github.com/joey711/phyloseq/wiki/ordinate) but it's still a little unclear as to how DPCoA differs from PCoA?

[spholmes]

You need to read this paper that lays it out very nicely:

http://www.ncbi.nlm.nih.gov/pubmed/22174277

On Wed, Aug 17, 2016 at 9:38 AM, nmshahir [email protected] wrote:

I'm going through the documentation (https://github.com/joey711/
phyloseq/wiki/ordinate) but it's still a little unclear as to how DPCoA
differs from PCoA?

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Sequoia Hall,
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[nmshahir]

Thank you @spholmes. I've gone through the paper and I have a few questions

1. It seems that instead of using UniFrac/weighted UniFrac as the distance metric, DPCoA utilizes a patristic distance as the metric?
2. The loadings corresponding to species loadings are name_of_dpcoa$dw , correct?
3. It was stated here ( Problem plotting OTUs with PCoA / MDS ordination #305 ), that you can also use CCA and RDA to obtain OTU loadings? Is there a particular benefit to using DPCoA over CCA and RDA? Or is it more of a case by case situation depending on the question you wish to ask?

Thank you!
-N

[spholmes]

1. It is correct, that is what DPCOA does uses first a patricstic distance
   to do a MDS/PCoA
   then take these points with the abundances as weights and compute the
   centres of gravities for sample point.

2. The loadings correspond to taxa as required.

3. If you consider the OTUs as independent categories it is fine to use
   Correspondence
   analyses (CCA without formula).

   Canonical correspondence analyses and RDA are quite different as they
   involve extra
   explanaotry variables/environmental factors/ etc..in a formula.

best
Susan

On Mon, Aug 22, 2016 at 7:53 PM, nmshahir [email protected] wrote:

Thank you @spholmes https://github.com/spholmes. I've gone through the
paper and I have a few questions

1. It seems that instead of using UniFrac/weighted UniFrac as the
   distance metric, DPCoA utilizes a patristic distance as the metric?
2. The loadings corresponding to species loadings are name_of_dpcoa$dw
   , correct?
3. It was stated here ( Problem plotting OTUs with PCoA / MDS ordination #305
   Problem plotting OTUs with PCoA / MDS ordination #305 ), that you can also
   use CCA and RDA to obtain OTU loadings? Is there a particular benefit to
   using DPCoA over CCA and RDA? Or is it more of a case by case situation
   depending on the question you wish to ask?

Thank you!
-N

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John Henry Samter Fellow in Undergraduate Education
Sequoia Hall,
390 Serra Mall
Stanford, CA 94305
http://www-stat.stanford.edu/~susan/