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update citation in documentation
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README.md

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@@ -18,8 +18,15 @@ in multiple populations). Multiple eigenvectors with elevated
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eigenvalues is indicative of multiple parallel/antiparallel axes within
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a genomic region, highlighting nonparallelism.
2020

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For more information on the software, please see the accompanying
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preprint: <https://www.biorxiv.org/content/10.1101/2021.09.17.460770v1>
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It is highly recommended to read the accompanying manuscript before
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applying this method. The manuscript is published in Methods in Ecology
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and Evolution (<https://doi.org/10.1111/2041-210X.13952>)
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### Citation
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Whiting, James R., Josephine R. Paris, Mijke J. van der Zee, and Bonnie A. Fraser. 2022.
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“AF‐vapeR : A Multivariate Genome Scan for Detecting Parallel Evolution Using Allele Frequency Change Vectors.”
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Methods in Ecology and Evolution / British Ecological Society, August. https://doi.org/10.1111/2041-210x.13952.
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<!-- ### Load from development dir -->
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<!-- ```{r} -->
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```
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## 95% 99% 99.9%
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## Eigenvector 1 3.473013 3.758088 3.943806
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## Eigenvector 2 3.837055 3.919276 3.984477
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## Eigenvector 3 3.958171 3.981431 3.995346
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## Eigenvector 1 3.469026 3.731064 3.940222
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## Eigenvector 2 3.831833 3.919587 3.984385
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## Eigenvector 3 3.958563 3.981497 3.995629
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## Eigenvector 4 4.000000 4.000000 4.000000
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Here, the values are summed through eigenvalues, such that the value for
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```
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## Eigenvalue_1 Eigenvalue_2 Eigenvalue_3 Eigenvalue_4
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## chr1:15-18166 0.00990099 0.00950095 0.02210221 0.5536554
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## chr1:18718-48277 0.80798080 0.57355736 0.71837184 0.8693869
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## chr1:48287-74923 0.24922492 0.47044704 0.45014501 0.6151615
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## chr1:75219-95836 0.93439344 0.97509751 0.94629463 0.1340134
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## chr1:96020-119073 0.27062706 0.30713071 0.25892589 0.6771677
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## chr1:119085-144327 0.12431243 0.08420842 0.10801080 0.2129213
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## chr1:15-18166 0.00890089 0.00960096 0.02240224 0.5487549
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## chr1:18718-48277 0.80468047 0.56935694 0.71587159 0.8722872
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## chr1:48287-74923 0.24472447 0.46474647 0.45114511 0.6120612
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## chr1:75219-95836 0.93329333 0.97729773 0.94709471 0.1333133
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## chr1:96020-119073 0.26822682 0.30383038 0.25612561 0.6781678
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## chr1:119085-144327 0.12231223 0.07890789 0.10491049 0.2092209
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Note: Because these empPvalues are calculated by comparing to the null
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distribution, they are bounded by the number of permutations. For
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```
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## $`Eigenvector 1`
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## [1] "chr1:9483266-9511933" "chr1:9973948-10015463" "chr1:10015604-10045407"
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## [4] "chr1:10045553-10083818" "chr2:9483266-9511933" "chr2:9973948-10015463"
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## [7] "chr2:10015604-10045407" "chr2:10045553-10083818" "chr3:9483266-9511933"
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## [10] "chr3:9973948-10015463" "chr3:10015604-10045407" "chr3:10045553-10083818"
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## [1] "chr1:9483266-9511933" "chr1:9883146-9904934" "chr1:9973948-10015463"
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## [4] "chr1:10015604-10045407" "chr1:10045553-10083818" "chr2:9483266-9511933"
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## [7] "chr2:9883146-9904934" "chr2:9973948-10015463" "chr2:10015604-10045407"
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## [10] "chr2:10045553-10083818" "chr3:9483266-9511933" "chr3:9883146-9904934"
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## [13] "chr3:9973948-10015463" "chr3:10015604-10045407" "chr3:10045553-10083818"
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##
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## $`Eigenvector 2`
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## [1] "chr1:9883146-9904934" "chr2:9883146-9904934" "chr3:9883146-9904934"
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## [1] "chr1:9925507-9947330" "chr2:9925507-9947330" "chr3:9925507-9947330"
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##
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## $`Eigenvector 3`
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## [1] "chr1:9904984-9925507" "chr2:9904984-9925507" "chr3:9904984-9925507"
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## window_id eigenvector eigenvalue parallel_lineages
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## 1 chr1:9483266-9511933 Eig1 3.945282 4
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## 2 chr1:9973948-10015463 Eig1 3.974657 4
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## 3 chr1:10015604-10045407 Eig1 3.972499 4
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## 4 chr1:10045553-10083818 Eig1 3.968457 4
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## 5 chr2:9483266-9511933 Eig1 3.945282 4
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## 6 chr2:9973948-10015463 Eig1 3.974657 4
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## 2 chr1:9883146-9904934 Eig1 3.941300 4
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## 3 chr1:9973948-10015463 Eig1 3.974657 4
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## 4 chr1:10015604-10045407 Eig1 3.972499 4
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## 5 chr1:10045553-10083818 Eig1 3.968457 4
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## 6 chr2:9483266-9511933 Eig1 3.945282 4
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## parallel_pops antiparallel_pops
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## 1 pop2,pop3,pop4,pop5
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## 2 pop2,pop3,pop4,pop5
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```
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## window_id eigenvector eigenvalue eigenvalue_sum parallel_lineages
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## 1 chr1:9883146-9904934 Eig1 3.9412997 3.985715 4
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## 2 chr1:9883146-9904934 Eig2 0.0444148 3.985715 2
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## 3 chr2:9883146-9904934 Eig1 3.9412997 3.985715 4
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## 4 chr2:9883146-9904934 Eig2 0.0444148 3.985715 2
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## 5 chr3:9883146-9904934 Eig1 3.9412997 3.985715 4
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## 6 chr3:9883146-9904934 Eig2 0.0444148 3.985715 2
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## 1 chr1:9925507-9947330 Eig1 3.92085336 3.984427 4
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## 2 chr1:9925507-9947330 Eig2 0.06357374 3.984427 2
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## 3 chr2:9925507-9947330 Eig1 3.92085336 3.984427 4
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## 4 chr2:9925507-9947330 Eig2 0.06357374 3.984427 2
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## 5 chr3:9925507-9947330 Eig1 3.92085336 3.984427 4
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## 6 chr3:9925507-9947330 Eig2 0.06357374 3.984427 2
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## parallel_pops antiparallel_pops
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## 1 pop2,pop3,pop4,pop5
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## 2 pop5 pop2
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## 2 pop2 pop5
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## 3 pop2,pop3,pop4,pop5
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## 4 pop5 pop2
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## 4 pop2 pop5
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## 5 pop2,pop3,pop4,pop5
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## 6 pop5 pop2
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## 6 pop2 pop5
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Interpreting these tables, the eigenvalues, and the distribution of
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parallel/antiparallel lineages, is key to filtering out regions that may

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