Entering edit mode
3.7 years ago
mariaemilyd
•
0
Hi,
I'm noticing something odd when I combine my 2 column allelic microsatellite dataset in R to 1 column with a separator (i.e. from locus1a: 100, locus1b: 90 to locus1: 100/90).
I've tried pegas::alleles2loci() and genetics::makeGenotypes() and noticed with both functions that for come loci in some rows, the order of the alleles switches when applying the functions, but it is not consistent (i.e. from locus1a: 100, locus1b: 90 to locus1: 90/10). I can't find any other help or documentation on why this occurs, can anyone help?
Code below:
library(strataG)
library(pegas)
library(genetics)
msat <- readGenData("./R_tarandus_Kluetsch_2017_microsats.csv")
str(msat)
'data.frame': 591 obs. of 20 variables:
$ indiv_id: chr "30554" "30555" "30559" "30560" ...
$ pop : chr "BAN" "BAN" "BAN" "BAN" ...
$ BM848a : chr "364" "362" "372" "386" ...
$ BM848b : chr "386" "372" "386" "386" ...
etc
head(msat)
indiv_id pop BM848a BM848b BM888a BM888b MAP2Ca MAP2Cb RT24a RT24b RT30a RT30b RT5a RT5b RT6a RT6b RT7a RT7b RT9a RT9b
1 30554 BAN 364 386 164 174 89 105 209 209 187 193 98 114 110 124 218 218 116 124
msat_loci <- pegas::alleles2loci(msat, ploidy = 2, rownames = 1, population = 2)
msat_gen <- genetics::makeGenotypes(msat, convert=list(3:4,5:6,7:8,9:10,11:12,13:14,15:16,17:18,19:20))
head(msat_gen)
indiv_id pop BM848a/BM848b BM888a/BM888b MAP2Ca/MAP2Cb RT24a/RT24b RT30a/RT30b RT5a/RT5b RT6a/RT6b RT7a/RT7b RT9a/RT9b
1 30554 BAN 386/364 174/164 105/89 209/209 193/187 114/98 110/124 218/218 116/124
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 14393)
Matrix products: default
locale:
[1] LC_COLLATE=English_United Kingdom.1252 LC_CTYPE=English_United Kingdom.1252 LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C LC_TIME=English_United Kingdom.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] genetics_1.3.8.1.2 mvtnorm_1.1-0 MASS_7.3-50 gtools_3.8.2 gdata_2.18.0 combinat_0.0-8
[7] HardyWeinberg_1.6.3 Rsolnp_1.16 mice_3.8.0 genepop_1.1.7 tidyr_1.0.2 purrr_0.3.4
[13] stringr_1.4.0 reshape_0.8.8 diffdf_1.0.4 kableExtra_1.1.0 dplyr_0.8.5 haplotypes_1.1.2
[19] pegas_0.13 adegenet_2.1.2 ade4_1.7-15 ape_5.3 strataG_2.4.905
loaded via a namespace (and not attached):
[1] colorspace_1.4-1 seqinr_3.6-1 deldir_0.1-25 ellipsis_0.3.0 class_7.3-14
[6] PopGenome_2.7.5 rstudioapi_0.11 spatstat.data_1.4-3 fansi_0.4.1 xml2_1.3.2
[11] codetools_0.2-15 splines_3.5.1 knitr_1.28 polyclip_1.10-0 swfscMisc_1.3
[16] broom_0.5.6 cluster_2.0.7-1 apex_1.0.4 shiny_1.4.0.2 readr_1.3.1
[21] compiler_3.5.1 httr_1.4.1 backports_1.1.6 assertthat_0.2.1 Matrix_1.2-14
[26] fastmap_1.0.1 cli_2.0.2 later_1.0.0 htmltools_0.4.0 tools_3.5.1
[31] igraph_1.2.5 coda_0.19-3 gtable_0.3.0 glue_1.4.0 reshape2_1.4.4
[36] maps_3.3.0 gmodels_2.18.1 tinytex_0.23 fastmatch_1.1-0 Rcpp_1.0.4.6
[41] spatstat_1.63-3 statnet.common_4.3.0 raster_3.1-5 vctrs_0.2.4 spdep_1.1-3
[46] nlme_3.1-137 xfun_0.14 network_1.16.0 rvest_0.3.5 mime_0.9
[51] mapdata_2.3.0 lifecycle_0.2.0 phangorn_2.5.5 goftest_1.2-2 LearnBayes_2.15.1
[56] scales_1.1.1 hms_0.5.3 promises_1.1.0 spatstat.utils_1.17-0 parallel_3.5.1
[61] expm_0.999-4 yaml_2.2.1 ggplot2_3.3.1 rpart_4.1-13 stringi_1.4.6
[66] plotrix_3.7-8 e1071_1.7-3 permute_0.9-5 boot_1.3-20 truncnorm_1.0-8
[71] spData_0.3.5 rlang_0.4.5 pkgconfig_2.0.3 evaluate_0.14 lattice_0.20-35
[76] tensor_1.5 sf_0.9-2 bit_1.1-15.2 tidyselect_1.0.0 plyr_1.8.6
[81] magrittr_1.5 R6_2.4.1 generics_0.0.2 sna_2.5 DBI_1.1.0
[86] pillar_1.4.4 mgcv_1.8-24 units_0.6-6 abind_1.4-5 sp_1.4-1
[91] tibble_3.0.1 crayon_1.3.4 KernSmooth_2.23-15 rmarkdown_2.2 grid_3.5.1
[96] data.table_1.12.8 vegan_2.5-6 digest_0.6.25 classInt_0.4-3 webshot_0.5.2
[101] xtable_1.8-4 ff_2.2-14.2 httpuv_1.5.2 munsell_0.5.0 viridisLite_0.3.0
[106] quadprog_1.5-8
