Reference 3 Admixture Error Estimation

Posted by on May 10, 2011

Since no one paid any attention to the error estimation results for reference I admixture, I am back with the standard error and bias estimates for reference 3 admixture.

So I ran the default 200 bootstrap replicates to measure standard error in our Reference 3 K=11 admixture. Spreadsheet with population level admixture results is here and participant results are here.

Here are some statistics for the standard error estimates:

Min. 1st Qu. Median Mean 3rd Qu. Max.
C1 S Asian 0 0.127 0.9848 0.7505 1.2216 1.6833
C2 Onge 0 0.2074 0.56 0.5404 0.8268 1.6914
C3 E Asian 0 0.2013 0.6123 0.6751 1.136 1.9961
C4 SW Asian 0 0.0874 1.1462 0.9246 1.5347 2.1008
C5 Euro 0 0.042 1.3034 0.9684 1.6582 2.3861
C6 Siberian 0 0.2054 0.6566 0.6712 1.0969 2.0099
C7 W African 0 0 0.01905 0.38847 0.75713 2.1588
C8 Papuan 0 0.1936 0.375 0.3648 0.5308 1.9627
C9 American 0 0.1461 0.3958 0.4646 0.6342 2.0831
C10 San/Pygmy 0 0 0.0708 0.2514 0.4471 2.0991
C11 E African 0 0 0.1235 0.3969 0.7315 1.9318

You can see the mean value of the standard errors per population and realize how many are over 1% (marked in red).

As the average error for the Onge component among South Asian populations is a little higher than 1%, the standard error on the ASI (Ancestral South Indian) computation here is about 1.4-1.5% just from admixture. The regression error is in addition to that.

And statistics for bias estimates:

Min. 1st Qu. Median Mean 3rd Qu. Max.
C1 -0.9069 -0.28408 -0.0349 -0.12196 0.01158 0.5856
C2 -0.7701 0 0.04005 0.03847 0.153 0.5703
C3 -0.5778 -0.0888 0.01645 0.02105 0.13737 0.6127
C4 -0.7701 -0.1657 0 -0.06692 0.01298 0.745
C5 -1.2917 -0.247675 0 -0.113631 0.008975 0.6763
C6 -0.7921 -0.0856 0.0129 0.009492 0.1198 0.6464
C7 -0.5745 0 0 -0.02173 0.0016 0.3426
C8 -0.1842 0.05328 0.13175 0.1377 0.21247 0.4712
C9 -0.4202 0.0096 0.0811 0.0915 0.1682 0.5129
C10 -0.4596 0 0.0002 0.003271 0.023425 0.3447
C11 -0.5766 0 0.0018 0.02276 0.05758 0.6346

You can also see the average value of the bias in each ancestral component for each population.

Admixture, , ,

3 Comments.

  1. Vasishta May 14, 2011 at 6:35 am

    Zack, answer this as I were a child, as Math has never been my stronghold - How exactly do you infer the possible errors for your own admixture scores, for let's say, the Ancestral South Indian component?

    • Vasishta May 14, 2011 at 6:36 am

      *as if
      **exactly do you infer/calculate

    • Zack May 15, 2011 at 11:00 am

      I can't claim any credit for the error estimates, it's part of Admixture software. I just got David to fix the crash for that procedure.

      It's basically a bootstrapping procedure where the software resamples the data to estimate its errors.

      Do you want details on the bootstrapping procedure?