Hi,

The improvement mentioned by Zhian is available in the version of pegas that is currently on GitHub (which will be the next version on CRAN).

Best,

Emmanuel

Le 15/02/2018 à 16:34, Zhian Kamvar a écrit :
Hi,

This is more of a question for the R-SIG-GENETICS group as it no longer deals with poppr any more, so I'm continuing it here. More knowledgable folk, feel free to correct me.

(1) Could I estimate the relative contribution of variances using SSD? e.g. 40434.10/77188.44=52.38%, It's the contribution of between groups variances?
sigma2 represents the variance, so you should use that to estimate relative contribution. The next version of pegas will present the phi values for you.

(2) What is the meaning of "sigma2" and "a"?
See above.

(3) Is P<0.05 conventionally enough to conclude significant difference for molecular data ? My result is 0.048 but I doubt it's power according to field observation. Should I set more strict critiria? 0.01 for example

I personally put very little trust in p-values for deciding on whether or not there is an effect. The choice of 0.05 as the cutoff is well-known to be arbitrary, so I think you should use your judgement of what you know about the natural history of these populations and your sample size to aid your conclusions.

Hope that helps,
Zhian

-----
Zhian N. Kamvar, Ph. D.
Postdoctoral Researcher (Everhart Lab)
Department of Plant Pathology
University of Nebraska-Lincoln
ORCID: 0000-0003-1458-7108




On Feb 13, 2018, at 23:00 , Yu NING <ningyu_s...@qq.com <mailto:ningyu_s...@qq.com>> wrote:

Hi, I have some difficulties in interpreting the result of AMOVA. The results show:
|
Bly_amova

Analysis of Molecular Variance

Call: pegas::amova(formula = Blygl_dis ~ popslot, data = strata(Bly_gl),
    is.squared = TRUE)

      SSD     MSD   df
popslot 40434.10 3110.316 13
Error   36754.33 1470.173 25
Total   77188.44 2031.275 38

Variance components:
       sigma2  P.value
popslot  589.75   0.048
Error   1470.17

Variance coefficients:
    a
2.781065
|

I wonder:

(1) Could I estimate the relative contribution of variances using SSD? e.g. 40434.10/77188.44=52.38%, It's the contribution of between groups variances?

(2) What is the meaning of "sigma2" and "a"?

(3) Is P<0.05 conventionally enough to conclude significant difference for molecular data ? My result is 0.048 but I doubt it's power according to field observation. Should I set more strict critiria? 0.01 for example

I've tried to searched for pegas tutorial or forum but failed. Any advice here will be highly appreciated. : )

在 2018年2月12日星期一 UTC+8下午11:31:06,Zhian Kamvar写道:

    Hello,

    I think I know why you were having this problem:

    1. You didn't have anything defined in your strata [1].
    2. You didn't have a variable called "pop" defined in your workspace
    3. Pegas saw a variable called "pop", which was a function, and
    gave a warning ("elements in the rhs of the formula are not all
    factors")

    However, given your code below, I'm not exactly sure why it works
    because "popslot" is not the same as "popslot_Kob". This tells me
    that you may run into problems in the future.

    You can define your strata with a data frame where each row
    represents a sample and each column is a different population
    grouping. A simple way to define it for the population:

    strata(Kob_snpclo) <-  data.frame(population = pop(Kob_snpclo))

    From there, you would use "population" on the right hand side of
    the formula in AMOVA.


    Cheers,
    Zhian

    [1]: If you are unfamiliar with strata, check out the strata
    tutorial:
    https://github.com/thibautjombart/adegenet/wiki/Tutorials
    <https://github.com/thibautjombart/adegenet/wiki/Tutorials>

    -----
    Zhian N. Kamvar, Ph. D.
    Postdoctoral Researcher (Everhart Lab)
    Department of Plant Pathology
    University of Nebraska-Lincoln
    ORCID: 0000-0003-1458-7108




    On Feb 12, 2018, at 04:47 , Yu NING <ningy...@qq.com
    <http://qq.com/>> wrote:

    Now I have found one way to work it out:
    |
    popslot_Kob<-pop(Kob_snpclo)
    Blygl_dis<-bitwise.dist(Bly_gl,percent=FALSE)
    
Bly_amova<-pegas::amova(Blygl_dis~popslot,data=strata(Bly_gl),is.squared=TRUE)
    |

    Just add one line to extract the pop information. But I still
    wonder why error showed when I use:
    |
    Bly_amova<-pegas::amova(Blygl_dis~pop,data=strata(Bly_gl),is.squared=TRUE)
    |

    It's a little wired....



    在 2018年2月11日星期日 UTC+8上午11:26:11,Yu NING写道:

        Hello,

        Thanks for your help. But other problems showed up:
        |
        > Blygl_dis<- bitwise.dist(Bly_gl, percent = FALSE)
        > Bly_amova<- pegas::amova(Blygl_dis ~ pop, data =
        strata(Bly_gl), is.squared = TRUE)
        Error in FUN(X[[i]], ...) : 'bin' must be numeric or a factor
        In addition: Warning message:
        In pegas::amova(Blygl_dis ~ pop, data = strata(Bly_gl),
        is.squared = TRUE) :
        elements in the rhs of the formula are not all factors
        |

        Is there something wrong in my data organization? This is the
        data info:
        |
        > Bly_gl
         /// GENLIGHT OBJECT /////////

         // 39 genotypes,  7,227 binary SNPs, size: 969.5 Kb
         11255 (3.99 %) missing data

         // Basic content
           @gen: list of 39 SNPbin
           @ploidy: ploidy of each individual  (range: 2-2)

         // Optional content
           @ind.names:  39 individual labels
           @loc.names:  7227 locus labels
           @chromosome: factor storing chromosomes of the SNPs
           @position: integer storing positions of the SNPs
           @pop: population of each individual (group size range: 2-3)
           @other: a list containing: elements without names
        |





        在 2018年1月23日星期二 UTC+8下午11:38:39,Zhian Kamvar写道:

            Hello,

            I have browsed the manual but I couldn't find how to
            calculate metrics of differentiation in/ poppr/ , and
            /poppr.amova()/ is also not applicable for snpclone
            object. Is there a way to solve it ?

            Unfortunately, calculating AMOVA on genlight objects is
            not currently possible in poppr [1]. I would recommend to
            use the pegas implementation like so:

            library("pegas")
            myDist <- bitwise.dist(myGenlight, percent = FALSE)
            res <- pegas::amova(myDist ~ pop/subpop, data =
            strata(myGenlight), is.squared = TRUE)

            Replace "myGenlight" with the name of your data and
            "pop/subpop" with the hierarchy present in your strata slot.


            Moreover, If I want to export my snpclone object which
is MLG filtered, how should I code?

            If you want to export the object for use in another
            Rscript, I would recommend using saveRDS() to save the
            object to a file and then readRDS() to read that file in
            a new session*. If you only need the MLG assignments,
            then he underlying genetic data does not change when you
            filter MLGs, so you can export the assignments as a CSV
            file along with your individual names and population data.

            I hope that helps.

            Zhian

            [1]: https://github.com/grunwaldlab/poppr/issues/72
            <https://github.com/grunwaldlab/poppr/issues/72>. This is
            not a simple problem and may still take a bit longer to
            implement as I am now only working on poppr in my spare time.
            * If you defined your MLGs using a matrix, then you must
            also save that matrix and reload it with the same name.


            -----
            Zhian N. Kamvar, Ph. D.
            Postdoctoral Researcher (Everhart Lab)
            Department of Plant Pathology
            University of Nebraska-Lincoln
            ORCID: 0000-0003-1458-7108




            On Jan 23, 2018, at 08:51 , Yu NING <ningy...@qq.com
            <http://qq.com/>> wrote:

            Hi~

            I have browsed the manual but I couldn't find how to
            calculate metrics of differentiation in/poppr/ ,
            and/poppr.amova()/is also not applicable for snpclone
            object. Is there a way to solve it ?  Moreover, If I
            want to export my snpclone object which is MLG filtered,
            how should I code? Thanks very much



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