YHPA.filtering

1 Yellow-headed Parrot (Amazona oratrix) SNP filtering and processing

Mexican towhees SNPfiltR vignette: https://devonderaad.github.io/towhees.uces/uce.processing/towhee.filt.html
SNPfiltR general package vignette: https://github.com/DevonDeRaad/SNPfiltR

Code

library(SNPfiltR)

This is SNPfiltR v.1.0.2

Detailed usage information is available at: devonderaad.github.io/SNPfiltR/ 

If you use SNPfiltR in your published work, please cite the following papers: 

DeRaad, D.A. (2022), SNPfiltR: an R package for interactive and reproducible SNP filtering. Molecular Ecology Resources, 22, 2443-2453. http://doi.org/10.1111/1755-0998.13618 

Knaus, Brian J., and Niklaus J. Grunwald. 2017. VCFR: a package to manipulate and visualize variant call format data in R. Molecular Ecology Resources, 17.1:44-53. http://doi.org/10.1111/1755-0998.12549

Code

library(vcfR)


   *****       ***   vcfR   ***       *****
   This is vcfR 1.15.0 
     browseVignettes('vcfR') # Documentation
     citation('vcfR') # Citation
   *****       *****      *****       *****

Code

library(ggplot2)
library(stringr)
library(StAMPP)

Loading required package: pegas

Loading required package: ape


Attaching package: 'pegas'

The following object is masked from 'package:ape':

    mst

The following objects are masked from 'package:vcfR':

    getINFO, write.vcf

Registered S3 method overwritten by 'ade4':
  method      from 
  print.amova pegas

Code

library(adegenet)

Loading required package: ade4


Attaching package: 'ade4'

The following object is masked from 'package:pegas':

    amova


   /// adegenet 2.1.11 is loaded ////////////

   > overview: '?adegenet'
   > tutorials/doc/questions: 'adegenetWeb()' 
   > bug reports/feature requests: adegenetIssues()

Code

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ tibble    3.3.0
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.0.4

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
✖ dplyr::where()  masks ape::where()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Code

vcfR <- read.vcfR("~/Dropbox/08_yhpa_072025/updated.54.amazona.oratrix.snps.unfiltered.vcf")

Code

vcfR

***** Object of Class vcfR *****
54 samples
1429 CHROMs
736,148 variants
Object size: 450.7 Mb
92.01 percent missing data
*****        *****         *****

Code

sample.info<-read.csv("~/Desktop/genomics/snp_calling/oratrix_nov2024/new_samples/clean_sample_info.csv")

#check vcf colnames
colnames(vcfR@gt)

 [1] "FORMAT"                "ao_ANSP_90568.sorted"  "ao_BC_107.sorted"     
 [4] "ao_BC_108.sorted"      "ao_BC_109.sorted"      "ao_BC_A112.sorted"    
 [7] "ao_BC_A113.sorted"     "ao_BC_A114.sorted"     "ao_BC_A115.sorted"    
[10] "ao_BC_A116.sorted"     "ao_BC_A117.sorted"     "ao_BC_A118.sorted"    
[13] "ao_LSUMZ_23890.sorted" "ao_LSUMZ_33050.sorted" "ao_LSUMZ_39731.sorted"
[16] "ao_LSUMZ_43831.sorted" "ao_LSUMZ_43832.sorted" "ao_MLZ_1105.sorted"   
[19] "ao_MLZ_32244.sorted"   "ao_MLZ_35920.sorted"   "ao_MLZ_39530.sorted"  
[22] "ao_MLZ_40633.sorted"   "ao_MLZ_40634.sorted"   "ao_MLZ_40635.sorted"  
[25] "ao_MLZ_41497.sorted"   "ao_MLZ_45517.sorted"   "ao_MLZ_48333.sorted"  
[28] "ao_MLZ_50773.sorted"   "ao_MLZ_50774.sorted"   "ao_MLZ_50775.sorted"  
[31] "ao_MLZ_59507.sorted"   "ao_MLZ_70063.sorted"   "ao_MLZ_70074.sorted"  
[34] "ao_SP_1.sorted"        "ao_SP_2.sorted"        "ao_SP_3.sorted"       
[37] "ao_SP_4.sorted"        "ao_SP_5.sorted"        "ao_SP_6.sorted"       
[40] "ao_SP_7.sorted"        "ao_SP_8.sorted"        "ao_SP_831.sorted"     
[43] "ao_SP_832.sorted"      "ao_SP_833.sorted"      "ao_SP_834.sorted"     
[46] "ao_SP_835.sorted"      "ao_SP_836.sorted"      "ao_SP_837.sorted"     
[49] "ao_SP_838.sorted"      "ao_SP_839.sorted"      "ao_SP_840.sorted"     
[52] "ao_UMMZ_103984.sorted" "ao_UMMZ_130517.sorted" "ao_UMMZ_95618.sorted" 
[55] "ao_UMMZ_95619.sorted"

Code

sample.info$Desired_Sequence_Name

 [1] "ao_ANSP_90568"  "ao_BC_107"      "ao_BC_108"      "ao_BC_109"     
 [5] "ao_BC_A112"     "ao_BC_A113"     "ao_BC_A114"     "ao_BC_A115"    
 [9] "ao_BC_A116"     "ao_BC_A117"     "ao_BC_A118"     "ao_B_719"      
[13] "ao_B_818"       "ao_LSUMZ_23890" "ao_LSUMZ_33050" "ao_LSUMZ_39731"
[17] "ao_LSUMZ_43831" "ao_LSUMZ_43832" "ao_MLZ_1105"    "ao_MLZ_32244"  
[21] "ao_MLZ_35920"   "ao_MLZ_39530"   "ao_MLZ_40633"   "ao_MLZ_40634"  
[25] "ao_MLZ_40635"   "ao_MLZ_41497"   "ao_MLZ_45517"   "ao_MLZ_48333"  
[29] "ao_MLZ_50773"   "ao_MLZ_50774"   "ao_MLZ_50775"   "ao_MLZ_59507"  
[33] "ao_MLZ_70063"   "ao_MLZ_70074"   "ao_SP_1"        "ao_SP_2"       
[37] "ao_SP_3"        "ao_SP_4"        "ao_SP_5"        "ao_SP_6"       
[41] "ao_SP_7"        "ao_SP_8"        "ao_SP_831"      "ao_SP_832"     
[45] "ao_SP_833"      "ao_SP_834"      "ao_SP_835"      "ao_SP_836"     
[49] "ao_SP_837"      "ao_SP_838"      "ao_SP_839"      "ao_SP_840"     
[53] "ao_SP_MA"       "ao_UMMZ_103984" "ao_UMMZ_130517" "ao_UMMZ_95618" 
[57] "ao_UMMZ_95619"

Code

#fix sample names
colnames(vcfR@gt)<-gsub(".sorted", "", colnames(vcfR@gt))
colnames(vcfR@gt)

 [1] "FORMAT"         "ao_ANSP_90568"  "ao_BC_107"      "ao_BC_108"     
 [5] "ao_BC_109"      "ao_BC_A112"     "ao_BC_A113"     "ao_BC_A114"    
 [9] "ao_BC_A115"     "ao_BC_A116"     "ao_BC_A117"     "ao_BC_A118"    
[13] "ao_LSUMZ_23890" "ao_LSUMZ_33050" "ao_LSUMZ_39731" "ao_LSUMZ_43831"
[17] "ao_LSUMZ_43832" "ao_MLZ_1105"    "ao_MLZ_32244"   "ao_MLZ_35920"  
[21] "ao_MLZ_39530"   "ao_MLZ_40633"   "ao_MLZ_40634"   "ao_MLZ_40635"  
[25] "ao_MLZ_41497"   "ao_MLZ_45517"   "ao_MLZ_48333"   "ao_MLZ_50773"  
[29] "ao_MLZ_50774"   "ao_MLZ_50775"   "ao_MLZ_59507"   "ao_MLZ_70063"  
[33] "ao_MLZ_70074"   "ao_SP_1"        "ao_SP_2"        "ao_SP_3"       
[37] "ao_SP_4"        "ao_SP_5"        "ao_SP_6"        "ao_SP_7"       
[41] "ao_SP_8"        "ao_SP_831"      "ao_SP_832"      "ao_SP_833"     
[45] "ao_SP_834"      "ao_SP_835"      "ao_SP_836"      "ao_SP_837"     
[49] "ao_SP_838"      "ao_SP_839"      "ao_SP_840"      "ao_UMMZ_103984"
[53] "ao_UMMZ_130517" "ao_UMMZ_95618"  "ao_UMMZ_95619"

Code

#make sure sampling file matches vcf
sample.info$Desired_Sequence_Name %in% colnames(vcfR@gt)[-1]

 [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
[13] FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
[25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
[37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
[49]  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE

Code

colnames(vcfR@gt)[-1] %in% sample.info$Desired_Sequence_Name

 [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[16] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[31] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[46] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE

Code

#reorder sampling file to match order of samples in vcf
sample.info<-sample.info[match(colnames(vcfR@gt)[-1], sample.info$Desired_Sequence_Name),]
sample.info$Desired_Sequence_Name == colnames(vcfR@gt)[-1]

 [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[16] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[31] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[46] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE

Code

vcfR<-filter_biallelic(vcfR)

269 SNPs, 0% of all input SNPs, contained more than 2 alleles, and were removed from the VCF

Code

vcfR

***** Object of Class vcfR *****
54 samples
1429 CHROMs
735,879 variants
Object size: 450 Mb
92.02 percent missing data
*****        *****         *****

Code

vcfR<-filter_allele_balance(vcfR)

21.19% of het genotypes (0.66% of all genotypes) fall outside of 0.25 - 0.75 allele balance ratio and were converted to NA

Code

vcfR

***** Object of Class vcfR *****
54 samples
1429 CHROMs
735,879 variants
Object size: 449.4 Mb
92.08 percent missing data
*****        *****         *****

Code

#set min and max depth cutoffs
vcfR<-hard_filter(vcfR, depth = 3)

38.73% of genotypes fall below a read depth of 3 and were converted to NA

no genotype quality cutoff provided, exploratory visualization will be generated.

Code

vcfR<-max_depth(vcfR, maxdepth = 100)

maxdepth cutoff is specified, filtered vcfR object will be returned

0.08% of SNPs were above a mean depth of 100 and were removed from the vcf

Code

vcfR

***** Object of Class vcfR *****
54 samples
1234 CHROMs
735,280 variants
Object size: 401.9 Mb
95.21 percent missing data
*****        *****         *****

Code

#remove invariant SNPs
vcfR<-min_mac(vcfR, min.mac = 1)

92.19% of SNPs fell below a minor allele count of 1 and were removed from the VCF

Code

vcfR

***** Object of Class vcfR *****
54 samples
987 CHROMs
57,410 variants
Object size: 61.8 Mb
54.28 percent missing data
*****        *****         *****

Code

#create popmap
popmap<-sample.info[sample.info$Desired_Sequence_Name %in% colnames(vcfR@gt)[-1],c(11,4)]
colnames(popmap)<-c("id","pop")
popmap$pop<-as.factor(popmap$pop)
popmap

               id                pop
1   ao_ANSP_90568           Yoro_Hon
2       ao_BC_107             Belize
3       ao_BC_108             Belize
4       ao_BC_109             Belize
5      ao_BC_A112             Belize
6      ao_BC_A113             Belize
7      ao_BC_A114             Belize
8      ao_BC_A115             Belize
9      ao_BC_A116             Belize
10     ao_BC_A117             Belize
11     ao_BC_A118             Belize
14 ao_LSUMZ_23890         Tabasco_MX
15 ao_LSUMZ_33050          Oaxaca_MX
16 ao_LSUMZ_39731         Chiapas_MX
17 ao_LSUMZ_43831          Colima_MX
18 ao_LSUMZ_43832          Colima_MX
19    ao_MLZ_1105       Socal_Parrot
20   ao_MLZ_32244      Tamaulipas_MX
21   ao_MLZ_35920        Veracruz_MX
22   ao_MLZ_39530      Tamaulipas_MX
23   ao_MLZ_40633      Tamaulipas_MX
24   ao_MLZ_40634      Tamaulipas_MX
25   ao_MLZ_40635      Tamaulipas_MX
26   ao_MLZ_41497 San Luis Potosi_MX
27   ao_MLZ_45517          Oaxaca_MX
28   ao_MLZ_48333      Tamaulipas_MX
29   ao_MLZ_50773        Guerrero_MX
30   ao_MLZ_50774        Guerrero_MX
31   ao_MLZ_50775        Guerrero_MX
32   ao_MLZ_59507        Veracruz_MX
33   ao_MLZ_70063       Socal_Parrot
34   ao_MLZ_70074       Socal_Parrot
35        ao_SP_1       Socal_Parrot
36        ao_SP_2       Socal_Parrot
37        ao_SP_3       Socal_Parrot
38        ao_SP_4       Socal_Parrot
39        ao_SP_5       Socal_Parrot
40        ao_SP_6       Socal_Parrot
41        ao_SP_7       Socal_Parrot
42        ao_SP_8       Socal_Parrot
43      ao_SP_831       Socal_Parrot
44      ao_SP_832       Socal_Parrot
45      ao_SP_833       Socal_Parrot
46      ao_SP_834       Socal_Parrot
47      ao_SP_835       Socal_Parrot
48      ao_SP_836       Socal_Parrot
49      ao_SP_837       Socal_Parrot
50      ao_SP_838       Socal_Parrot
51      ao_SP_839       Socal_Parrot
52      ao_SP_840       Socal_Parrot
54 ao_UMMZ_103984         Tabasco_MX
55 ao_UMMZ_130517       Michoacan_MX
56  ao_UMMZ_95618         Nayarit_MX
57  ao_UMMZ_95619         Nayarit_MX

Code

#add in locality to sample name for PCA label
popmap$new_id<-c("Honduras_ao_ANSP_90568",
                 "Belize_BC_107",
                 "Belize_BC_108",
                 "Belize_BC_109",
                 "Belize_BC_A112",
                 "Belize_BC_A113",
                 "Belize_BC_A114",
                 "Belize_BC_A115",
                 "Belize_BC_A116",
                 "Belize_BC_A117",
                 "Belize_BC_A118",
                 "Tabasco_LSUMZ_23890",
                 "Oaxaca_LSUMZ_33050",
                 "Chiapas_LSUMZ_39731",
                 "Colima_LSUMZ_43831",
                 "Colima_LSUMZ_43832",
                 "SCP_MLZ_1105",
                 "Tamaulipas_MLZ_32244",
                 "Veracruz_MLZ_35920",
                 "Tamaulipas_MLZ_39530",
                 "Tamaulipas_MLZ_40633",
                 "Tamaulipas_MLZ_40634",
                 "Tamaulipas_MLZ_40635",
                 "San_Luis_Potosi_MLZ_41497",
                 "Oaxaca_MLZ_45517",
                 "Tamaulipas_MLZ_48333",
                 "Guerrero_MLZ_50773",
                 "Guerrero_MLZ_50774",
                 "Guerrero_MLZ_50775",
                 "Veracruz_MLZ_59507",
                 "SCP_MLZ_70063",
                 "SCP_MLZ_70074",
                 "SCP_SP_1",
                 "SCP_SP_2",
                 "SCP_SP_3",
                 "SCP_SP_4",
                 "SCP_SP_5",
                 "SCP_SP_6",
                 "SCP_SP_7",
                 "SCP_SP_8",
                 "SCP_SP_831",
                 "SCP_SP_832",
                 "SCP_SP_833",
                 "SCP_SP_834",
                 "SCP_SP_835",
                 "SCP_SP_836",
                 "SCP_SP_837",
                 "SCP_SP_838",
                 "SCP_SP_839",
                 "SCP_SP_840",
                 "Tabasco_UMMZ_103984",
                 "Michoacán_UMMZ_130517",
                 "Nayarit_UMMZ_95618",
                 "Nayarit_UMMZ_95619")

popmap

               id                pop                    new_id
1   ao_ANSP_90568           Yoro_Hon    Honduras_ao_ANSP_90568
2       ao_BC_107             Belize             Belize_BC_107
3       ao_BC_108             Belize             Belize_BC_108
4       ao_BC_109             Belize             Belize_BC_109
5      ao_BC_A112             Belize            Belize_BC_A112
6      ao_BC_A113             Belize            Belize_BC_A113
7      ao_BC_A114             Belize            Belize_BC_A114
8      ao_BC_A115             Belize            Belize_BC_A115
9      ao_BC_A116             Belize            Belize_BC_A116
10     ao_BC_A117             Belize            Belize_BC_A117
11     ao_BC_A118             Belize            Belize_BC_A118
14 ao_LSUMZ_23890         Tabasco_MX       Tabasco_LSUMZ_23890
15 ao_LSUMZ_33050          Oaxaca_MX        Oaxaca_LSUMZ_33050
16 ao_LSUMZ_39731         Chiapas_MX       Chiapas_LSUMZ_39731
17 ao_LSUMZ_43831          Colima_MX        Colima_LSUMZ_43831
18 ao_LSUMZ_43832          Colima_MX        Colima_LSUMZ_43832
19    ao_MLZ_1105       Socal_Parrot              SCP_MLZ_1105
20   ao_MLZ_32244      Tamaulipas_MX      Tamaulipas_MLZ_32244
21   ao_MLZ_35920        Veracruz_MX        Veracruz_MLZ_35920
22   ao_MLZ_39530      Tamaulipas_MX      Tamaulipas_MLZ_39530
23   ao_MLZ_40633      Tamaulipas_MX      Tamaulipas_MLZ_40633
24   ao_MLZ_40634      Tamaulipas_MX      Tamaulipas_MLZ_40634
25   ao_MLZ_40635      Tamaulipas_MX      Tamaulipas_MLZ_40635
26   ao_MLZ_41497 San Luis Potosi_MX San_Luis_Potosi_MLZ_41497
27   ao_MLZ_45517          Oaxaca_MX          Oaxaca_MLZ_45517
28   ao_MLZ_48333      Tamaulipas_MX      Tamaulipas_MLZ_48333
29   ao_MLZ_50773        Guerrero_MX        Guerrero_MLZ_50773
30   ao_MLZ_50774        Guerrero_MX        Guerrero_MLZ_50774
31   ao_MLZ_50775        Guerrero_MX        Guerrero_MLZ_50775
32   ao_MLZ_59507        Veracruz_MX        Veracruz_MLZ_59507
33   ao_MLZ_70063       Socal_Parrot             SCP_MLZ_70063
34   ao_MLZ_70074       Socal_Parrot             SCP_MLZ_70074
35        ao_SP_1       Socal_Parrot                  SCP_SP_1
36        ao_SP_2       Socal_Parrot                  SCP_SP_2
37        ao_SP_3       Socal_Parrot                  SCP_SP_3
38        ao_SP_4       Socal_Parrot                  SCP_SP_4
39        ao_SP_5       Socal_Parrot                  SCP_SP_5
40        ao_SP_6       Socal_Parrot                  SCP_SP_6
41        ao_SP_7       Socal_Parrot                  SCP_SP_7
42        ao_SP_8       Socal_Parrot                  SCP_SP_8
43      ao_SP_831       Socal_Parrot                SCP_SP_831
44      ao_SP_832       Socal_Parrot                SCP_SP_832
45      ao_SP_833       Socal_Parrot                SCP_SP_833
46      ao_SP_834       Socal_Parrot                SCP_SP_834
47      ao_SP_835       Socal_Parrot                SCP_SP_835
48      ao_SP_836       Socal_Parrot                SCP_SP_836
49      ao_SP_837       Socal_Parrot                SCP_SP_837
50      ao_SP_838       Socal_Parrot                SCP_SP_838
51      ao_SP_839       Socal_Parrot                SCP_SP_839
52      ao_SP_840       Socal_Parrot                SCP_SP_840
54 ao_UMMZ_103984         Tabasco_MX       Tabasco_UMMZ_103984
55 ao_UMMZ_130517       Michoacan_MX     Michoacán_UMMZ_130517
56  ao_UMMZ_95618         Nayarit_MX        Nayarit_UMMZ_95618
57  ao_UMMZ_95619         Nayarit_MX        Nayarit_UMMZ_95619

Code

assess_missing_data_pca(vcfR = vcfR, popmap = popmap, thresholds = c(0.8, 0.9), clustering = FALSE)

cutoff is specified, filtered vcfR object will be returned

Warning: Removed 1 row containing missing values or values outside the scale range
(`geom_point()`).

74.05% of SNPs fell below a completeness cutoff of 0.8 and were removed from the VCF

cutoff is specified, filtered vcfR object will be returned

Warning: Removed 1 row containing missing values or values outside the scale range
(`geom_point()`).

89.38% of SNPs fell below a completeness cutoff of 0.9 and were removed from the VCF

[[1]]
                       PC1          PC2          PC3          PC4         PC5
ao_ANSP_90568   0.06145779  0.005902713  0.005256615  0.004069377  0.02276869
ao_BC_107      -1.64121827 -1.613991369 -2.338909535 -3.311219522 -0.82202174
ao_BC_108      -1.54869901 -1.571506227 -2.217369229 -3.249091960 -0.75457952
ao_BC_109      -1.51103041 -1.422266809 -1.926448518 -3.290854879 -0.83574268
ao_BC_A112     -0.33523208 -0.435406670 -0.146407843 -0.377081940 -0.06997520
ao_BC_A113     -1.57654535 -1.022155832 -1.681000579 -2.767992724 -0.48321467
ao_BC_A114     -1.62664206 -1.320754903 -2.241644146 -3.121433041 -0.63074672
ao_BC_A115     -1.66887765 -1.670150347 -2.259689393 -3.601369902 -0.81918798
ao_BC_A116     -1.56156007 -1.342673006 -1.650033485 -2.591354140 -0.56300918
ao_BC_A117     -1.52132325 -1.324482056 -1.161759786 -2.768279444 -0.53992195
ao_BC_A118     -1.62743542 -1.300847891 -1.483383498 -2.736904946 -0.54903486
ao_LSUMZ_23890  0.50840646 -0.024043833  0.045238339  0.098159554  0.44906025
ao_LSUMZ_33050 -1.59036324  6.120051869  1.433770843 -0.764001477 -0.72423245
ao_LSUMZ_39731 -1.59568806  1.735293217 -0.549734839 -1.675345995  1.17453160
ao_LSUMZ_43831 -1.55113776  5.872505351  1.857172340 -1.312230458 -0.52911740
ao_LSUMZ_43832 -1.55917562  6.192512339  1.683757233 -1.426556556 -0.80226439
ao_MLZ_1105    -1.55837089 -1.194947479  1.270710772  1.408181854 -0.16351577
ao_MLZ_32244   71.42979871 -0.056186894 -0.002990597  0.004613764 -0.51161275
ao_MLZ_35920   -0.80665838 -1.117455791  0.760531139  0.407245233  0.08180193
ao_MLZ_39530   -0.24207267 -0.036514715  0.228311634  0.229963063  0.61553812
ao_MLZ_40633   -0.17753088 -0.610259841  0.783137815  0.820573680  1.44773256
ao_MLZ_40634   -1.54757027 -0.692283711  0.404201800  1.420284728  0.22340145
ao_MLZ_40635    0.59052824  0.016186033 -0.327115676 -0.204772660  8.89092726
ao_MLZ_41497   -1.37071036 -0.783516840  1.737621400  1.324399600  0.42493318
ao_MLZ_45517    0.14464757  1.266385435 -1.338419321 -0.640508731  7.86575490
ao_MLZ_48333   -1.37332809 -0.707554466  0.657971682  1.654528002  0.30836645
ao_MLZ_50773   -1.24555867  6.260162449  2.046960028 -0.642228592 -0.36937695
ao_MLZ_50774   -1.48410157  5.445551388  1.654462872 -0.880931983 -0.46631546
ao_MLZ_50775   -1.58061958  5.950116784  1.869858928 -0.538408771 -0.79783989
ao_MLZ_59507   -1.05680294 -1.307813099  0.548497645  0.780067612 -0.19825101
ao_MLZ_70063   -1.51075388 -0.966594948  1.435813858  1.677672292  0.28683351
ao_MLZ_70074   -1.56121107 -0.915784410  0.635627183  1.223610051  0.06820427
ao_SP_1        -1.63167882 -1.359722058  0.348100444  1.001161550 -0.25016913
ao_SP_2        -1.64291941 -1.444654604  0.723279991  1.346958375 -0.48665050
ao_SP_3        -1.63692062 -1.357410784  0.416282424  1.019689985 -0.41701181
ao_SP_4        -1.64773581 -1.671306157  0.476619757  1.400755783 -0.47001416
ao_SP_5        -1.67490370 -1.281060941  0.590284074  1.082665398 -0.46239527
ao_SP_6        -1.64976804 -1.761109188  1.117688408  1.200928586 -0.52045813
ao_SP_7        -1.67092806 -2.357907530  1.338016897  1.473627645 -0.63554823
ao_SP_8        -1.66453904 -1.454468908  0.862056377  0.396165927 -0.30627911
ao_SP_831      -1.68662266 -1.353668774  0.719216706  0.044168817 -0.47825019
ao_SP_832      -1.70367473 -2.004694900  0.624099286  0.790994103 -0.52163342
ao_SP_833      -1.66229808 -1.845079399  0.196400447  1.076716591 -0.62548043
ao_SP_834      -1.64192917 -1.858282043  0.521763629  0.904292870 -0.50240214
ao_SP_835      -1.69337918 -2.570287756  1.137539836  1.648573921 -0.69799791
ao_SP_836      -1.64545275 -2.404289740  0.697439924  0.366448352 -0.46582176
ao_SP_837      -1.63095825 -1.675319716  0.838489341  0.858032415 -0.29440502
ao_SP_838      -1.62195166 -1.604550918  0.800963240  1.273356293 -0.21794038
ao_SP_839      -1.68953114 -1.911833895  0.412876470  0.245042436 -0.29395918
ao_SP_840      -1.68971866 -1.519284762  0.975126113  0.577278974 -0.74445894
ao_UMMZ_103984 -1.63541247 -1.128364009 -0.118936363 -0.246908948 -0.30168271
ao_UMMZ_130517 -1.58285003  6.002722822  1.962008406 -0.806422927 -0.62883017
ao_UMMZ_95618  -1.59463431  4.377129565 -6.929187166  4.556232923 -0.93439672
ao_UMMZ_95619  -1.60681471  4.755967253 -7.444123923  4.637439844 -0.97410829
                        PC6          PC7          PC8         PC9        PC10
ao_ANSP_90568  -0.013279738 -0.009175023  0.005081794 -0.01431648 -0.01953191
ao_BC_107       0.398463140  0.268708890 -0.413149964 -1.97768890  1.01421738
ao_BC_108       0.317900626  0.687750159 -0.313982730 -1.90374863  1.03297755
ao_BC_109       0.308806317  1.050978230 -0.713981795 -1.69798886  1.44327537
ao_BC_A112      0.130752209  0.010350925 -0.072657308 -0.11441571  0.20975446
ao_BC_A113      0.122232459  0.741393339  0.064148095  0.94330679  0.88962104
ao_BC_A114      0.257609786 -0.077986150  0.573196031  0.16837736 -2.71282519
ao_BC_A115      0.355638513  0.045326874  0.133456477 -0.50145304 -2.71266800
ao_BC_A116      0.072370352  0.319878801 -0.548270330  0.18320695  0.36471355
ao_BC_A117      0.032954229  0.562529300  0.260397849  1.03566763  0.06241150
ao_BC_A118      0.046535839 -0.020011601 -0.526900627  0.96321782  1.20780405
ao_LSUMZ_23890  0.118709613  0.047454175  0.259695772 -0.47427327 -0.48258796
ao_LSUMZ_33050  0.264970065  0.117782559 -0.307267187 -0.22527031  0.24985261
ao_LSUMZ_39731 -2.319638689 -0.039154903  0.277056911  6.86212737  3.20413827
ao_LSUMZ_43831  0.109341355 -0.379861989 -0.230553104  0.08068912 -0.58584278
ao_LSUMZ_43832  0.271660091 -0.265578011 -0.297353808 -0.26246699 -1.10594718
ao_MLZ_1105    -0.157605643  2.607291749  0.238148778 -0.11697727  1.44675630
ao_MLZ_32244   -0.043911115 -0.086425240 -0.025234572  0.08074115  0.02574819
ao_MLZ_35920   -0.150336125  0.498942600  1.760790514 -1.12193193 -0.43732675
ao_MLZ_39530   -0.097600271  1.187527235  1.097817395  0.48235369 -0.22660273
ao_MLZ_40633   -0.218553427  4.112579235 -0.519606865 -1.05408636  0.53070555
ao_MLZ_40634   -0.075021213  3.417582499  0.515830096 -0.65880582  0.92175698
ao_MLZ_40635    7.857303286 -0.700240246 -0.338759429  0.51567266  0.21914476
ao_MLZ_41497   -0.579897520  4.351615080  0.419643207  0.19988626 -0.01060334
ao_MLZ_45517   -7.958573791 -1.886858256 -0.225754846 -1.94544157 -0.60265378
ao_MLZ_48333   -0.405830577  2.590449566  0.576647569 -0.19868898 -0.27895295
ao_MLZ_50773    0.503080796 -0.951536276 -0.343206458 -1.89869808  0.36747967
ao_MLZ_50774    0.120442077 -0.511356100 -0.147498936 -0.06504146  0.28355046
ao_MLZ_50775    0.339811852 -0.101809346  0.075572666 -0.12195157  0.63135034
ao_MLZ_59507    0.307337828 -0.534530813  0.280875349  0.05487701 -1.81273579
ao_MLZ_70063   -0.715807843  2.946500822 -1.061582009  0.08846778 -0.18744366
ao_MLZ_70074   -0.391756189  2.900812919  0.132619400  0.36732832 -1.69132585
ao_SP_1        -0.081108408 -0.986517935  0.841229168  1.09113238 -0.84626265
ao_SP_2         0.034068182 -2.008299186  1.024288543  0.26500553 -1.10695033
ao_SP_3        -0.084368655 -0.628575123 -0.449477198  0.21938668 -0.18819567
ao_SP_4         0.208830161 -1.657093719  3.723240069 -1.44993607  2.67435396
ao_SP_5         0.150341800 -1.935321257  1.760019801 -0.19211727 -1.29809479
ao_SP_6         0.091824817 -1.095932879 -1.385126727  0.60199506 -0.92030378
ao_SP_7        -0.060504647 -1.603102261 -4.661093921 -1.00813997  1.68944645
ao_SP_8        -0.069299200 -0.222888036 -1.052679142  0.75174632 -2.12459213
ao_SP_831       0.027517969 -1.583825831  0.820377526  0.69596452 -0.04929513
ao_SP_832      -0.004029975 -1.635277613  0.678220363 -0.03943350  0.70039022
ao_SP_833       0.282113607 -2.039576608  3.492526888 -1.65334718  2.90907202
ao_SP_834      -0.103309780 -0.719969501 -0.158872647  0.18218973 -0.04160359
ao_SP_835      -0.065322539 -1.877761117 -4.901998753 -0.68754220  1.57845118
ao_SP_836       0.031869892 -0.726188577 -0.811387208  1.25186215 -1.30561304
ao_SP_837      -0.037823027 -1.064440626  0.598248229  0.94464670 -0.93365878
ao_SP_838      -0.196689881 -0.592673400  0.760014585  0.27727882 -0.16488368
ao_SP_839      -0.098993949 -0.781883865 -0.447058943  0.24953294 -0.51402883
ao_SP_840       0.110822768 -1.366360927 -0.311962106  0.22545630  0.18238786
ao_UMMZ_103984 -0.019578475 -0.118273184  0.337191197  0.43306182 -1.03538784
ao_UMMZ_130517  0.271419825 -0.175869192  0.381289991 -0.10911691 -0.25424472
ao_UMMZ_95618   0.414139335 -0.074294632 -0.475512472  0.05891196  0.20589492
ao_UMMZ_95619   0.389971889 -0.006805533 -0.346695178  0.21878751 -0.39509176
                      PC11         PC12         PC13         PC14        PC15
ao_ANSP_90568   0.06831645  0.035724120 -0.005724775  0.048747736 -0.02660719
ao_BC_107      -0.61978732 -0.020716631  0.970440516  0.483297237 -0.08553748
ao_BC_108      -0.71370305 -0.323163961  1.180061781  1.586640991  0.33730492
ao_BC_109      -0.61441283 -0.306539635  1.275897059  1.407308175 -0.22821255
ao_BC_A112      0.03850791  0.003925994 -0.029813231  0.254460089 -0.02815530
ao_BC_A113     -0.43246386  1.282652034 -0.219084369  0.205831550 -0.05642875
ao_BC_A114      0.65825823 -1.520747564 -1.568540768 -1.929502813  0.54580961
ao_BC_A115      0.79904273 -2.198539760 -1.616652817 -2.791226811  1.00121665
ao_BC_A116     -0.08229433  0.569182371 -0.058418676  0.216235111 -0.85329296
ao_BC_A117      0.22282004  0.403055556 -0.379445962  0.222125076 -0.77643992
ao_BC_A118     -0.36745715  1.380681375 -0.234372634  0.220634537 -0.21526674
ao_LSUMZ_23890  7.32484322  1.871540441  2.636313181  1.395004677  1.97403492
ao_LSUMZ_33050 -0.22554533  0.658733732  0.382304105 -0.772513106 -1.41610621
ao_LSUMZ_39731  1.34960182 -1.374676727 -1.103974419 -0.273700255  0.03877264
ao_LSUMZ_43831 -0.71722633  0.384288893  1.313965894 -1.018953255  1.33005435
ao_LSUMZ_43832 -0.88132653  0.983390817  1.376887254 -1.369903432  1.15385266
ao_MLZ_1105    -0.39407945 -0.841829249  1.237426968 -0.275718143  0.03791859
ao_MLZ_32244   -0.21394045 -0.135737485  0.009699694 -0.043940093  0.01755420
ao_MLZ_35920    2.41480507 -0.272041170 -0.212806487 -1.803359786 -3.34546458
ao_MLZ_39530   -0.11049404  0.924014499 -0.248579516  0.039775096 -1.55577013
ao_MLZ_40633   -0.11283659  5.027712464 -4.692678312 -0.686353951  1.78789591
ao_MLZ_40634    0.05956554 -0.933699899  0.490073005 -1.049863226 -0.89159343
ao_MLZ_40635   -0.42195226 -0.552556170  0.382929796 -0.201138121  0.05856614
ao_MLZ_41497   -0.23855354 -1.478234202  0.394451940  1.117866245 -0.41451136
ao_MLZ_45517   -0.66442032 -0.023313428  0.482897641 -0.010935447 -0.12775689
ao_MLZ_48333   -0.38056477 -1.555882226  0.574535345  0.362752545 -1.28263694
ao_MLZ_50773    1.34769739 -3.238777062 -4.469968467  4.455708357  0.20149545
ao_MLZ_50774   -0.10235725  0.225108055  0.507476319 -0.864774819 -0.89388353
ao_MLZ_50775   -0.28027737  0.506875620  0.337428591 -1.178667637 -0.68816100
ao_MLZ_59507    0.26941522  1.564689046 -0.088725384  1.118149480 -4.39279519
ao_MLZ_70063   -0.41412915 -1.734521452  1.014644245 -0.306061804  2.05591811
ao_MLZ_70074   -0.26076509 -1.274138910  0.430176480 -0.199919260  1.80157627
ao_SP_1        -0.53736089  0.847605145  0.151717607  1.014095734 -0.18729732
ao_SP_2        -0.43853720  0.084942843 -0.431179098  0.002042804  0.60990387
ao_SP_3        -0.41397058 -0.339032589  0.749629768  0.479871870 -0.37295536
ao_SP_4        -0.12736871 -0.326832710 -0.316393573 -1.016937205  0.28200744
ao_SP_5        -0.01885383 -0.178289080 -1.092584667 -0.514959491  0.81947962
ao_SP_6         0.24770001 -0.393827593 -0.080666717 -0.556002139 -0.32700364
ao_SP_7         0.67759727 -0.559105757 -0.343810786 -1.371173211 -0.49457915
ao_SP_8        -0.55942417  0.449504800  0.130802575  0.696824473 -0.19039659
ao_SP_831      -1.02298339  0.035896086  1.081027122  1.537496042  1.44230306
ao_SP_832      -0.42739310  0.254040878  0.237310772 -0.916500978  1.38989659
ao_SP_833      -0.11261868 -0.032774695 -0.445704317 -0.893797773  0.73524555
ao_SP_834      -1.06152524  0.457827937  0.534221024  1.024701439  1.23852806
ao_SP_835       0.74148956 -0.428079796 -0.582542279 -1.510562180 -0.42834032
ao_SP_836      -0.79694638  1.098084333  0.052978443  1.494869047  0.51316526
ao_SP_837      -0.65299695  0.540830774  0.185521290  1.353390595 -0.47397577
ao_SP_838       0.07090849 -0.421889575 -0.524467206 -0.776352913  0.15020703
ao_SP_839      -0.85537211  0.890683454 -0.082826551  0.952966595  0.07033044
ao_SP_840      -0.08994075 -0.268810415 -0.062481753  0.135066224  0.32458896
ao_UMMZ_103984 -0.07591858 -0.523371110  0.124390442  0.224846865 -0.60209804
ao_UMMZ_130517 -0.59783973  0.635113680  0.709283879  0.098402197  0.33071030
ao_UMMZ_95618  -0.07713199  0.064723839 -0.162664316  0.118787088  0.19158433
ao_UMMZ_95619  -0.17579966  0.076300065  0.099614345  0.064919977 -0.08465457
                              pop      missing
ao_ANSP_90568            Yoro_Hon 9.897288e-01
ao_BC_107                  Belize 3.020945e-03
ao_BC_108                  Belize 7.236842e-02
ao_BC_109                  Belize 6.719925e-02
ao_BC_A112                 Belize 7.686627e-01
ao_BC_A113                 Belize 3.108217e-02
ao_BC_A114                 Belize 9.465628e-03
ao_BC_A115                 Belize 3.155209e-03
ao_BC_A116                 Belize 2.846402e-02
ao_BC_A117                 Belize 6.605800e-02
ao_BC_A118                 Belize 9.734157e-03
ao_LSUMZ_23890         Tabasco_MX 9.682465e-01
ao_LSUMZ_33050          Oaxaca_MX 1.275510e-03
ao_LSUMZ_39731         Chiapas_MX 5.437701e-03
ao_LSUMZ_43831          Colima_MX 1.705156e-02
ao_LSUMZ_43832          Colima_MX 2.289205e-02
ao_MLZ_1105          Socal_Parrot 1.342642e-04
ao_MLZ_32244        Tamaulipas_MX 5.437701e-02
ao_MLZ_35920          Veracruz_MX 2.721536e-01
ao_MLZ_39530        Tamaulipas_MX 5.904941e-01
ao_MLZ_40633        Tamaulipas_MX 4.769066e-01
ao_MLZ_40634        Tamaulipas_MX 6.914608e-03
ao_MLZ_40635        Tamaulipas_MX 8.758727e-01
ao_MLZ_41497   San Luis Potosi_MX 4.048067e-02
ao_MLZ_45517            Oaxaca_MX 5.300752e-01
ao_MLZ_48333        Tamaulipas_MX 4.296455e-02
ao_MLZ_50773          Guerrero_MX 8.069280e-02
ao_MLZ_50774          Guerrero_MX 3.443878e-02
ao_MLZ_50775          Guerrero_MX 3.625134e-03
ao_MLZ_59507          Veracruz_MX 1.734023e-01
ao_MLZ_70063         Socal_Parrot 6.713212e-05
ao_MLZ_70074         Socal_Parrot 6.713212e-05
ao_SP_1              Socal_Parrot 3.826531e-03
ao_SP_2              Socal_Parrot 1.275510e-03
ao_SP_3              Socal_Parrot 8.727175e-04
ao_SP_4              Socal_Parrot 9.398496e-04
ao_SP_5              Socal_Parrot 2.483888e-03
ao_SP_6              Socal_Parrot 1.409774e-03
ao_SP_7              Socal_Parrot 2.013963e-04
ao_SP_8              Socal_Parrot 8.727175e-04
ao_SP_831            Socal_Parrot 6.713212e-05
ao_SP_832            Socal_Parrot 6.713212e-04
ao_SP_833            Socal_Parrot 1.342642e-04
ao_SP_834            Socal_Parrot 4.027927e-04
ao_SP_835            Socal_Parrot 1.342642e-04
ao_SP_836            Socal_Parrot 2.013963e-04
ao_SP_837            Socal_Parrot 0.000000e+00
ao_SP_838            Socal_Parrot 2.685285e-04
ao_SP_839            Socal_Parrot 4.027927e-04
ao_SP_840            Socal_Parrot 6.713212e-05
ao_UMMZ_103984         Tabasco_MX 1.074114e-03
ao_UMMZ_130517       Michoacan_MX 3.826531e-03
ao_UMMZ_95618          Nayarit_MX 8.727175e-04
ao_UMMZ_95619          Nayarit_MX 5.370569e-04

[[2]]
                        PC1          PC2          PC3          PC4          PC5
ao_ANSP_90568   -0.04559060  0.007932244  0.001156137  0.019908130  0.021482246
ao_BC_107        0.82569071 -1.039663825  0.092103476  1.070198560 -1.198288159
ao_BC_108        0.83536005 -1.010396571  0.092175486  1.027523875 -1.108018979
ao_BC_109        0.84828875 -1.001150550  0.194184644  0.733036398 -0.904011857
ao_BC_A112       0.30742498 -0.411186078  0.069825259  0.147335883 -0.268771200
ao_BC_A113       0.81129702 -0.688789486  0.095834884  0.929725302 -1.230424426
ao_BC_A114       0.83002310 -0.647940096  0.094298883  0.854109573 -1.216813052
ao_BC_A115       0.89331486 -1.192388626  0.113911249  1.076389252 -1.492623958
ao_BC_A116       0.83730506 -0.712446418  0.173636799  0.591331480 -0.847109676
ao_BC_A117       0.84180655 -0.617172933  0.215202218  0.844793663 -0.895853348
ao_BC_A118       0.84515365 -0.958030662  0.188452110  0.938071860 -1.222626036
ao_LSUMZ_23890  -0.60711749  0.028281543 -0.198528063  0.137981671  0.140809935
ao_LSUMZ_33050   0.79984087  3.457124708  0.572910419  0.338519659 -0.916244240
ao_LSUMZ_39731   0.86653577  1.277903215 -0.074630996  1.382042256  0.005966826
ao_LSUMZ_43831   0.82572494  3.110698630  0.533502918  0.536100348 -1.106157326
ao_LSUMZ_43832   0.85156546  3.433307031  0.670391463  0.559842779 -1.407096015
ao_MLZ_1105      0.79376704 -0.684945142  0.320011294 -0.728461158  0.561276802
ao_MLZ_32244   -38.02206563 -0.040820690  0.398705251 -0.025972945 -0.052312484
ao_MLZ_35920     0.72923537 -0.529750268  0.126709502 -0.084005491  0.432484608
ao_MLZ_39530     0.35701978 -0.064965663 -0.401551200 -0.622659252  0.742592460
ao_MLZ_40633     0.33282781 -0.396181972 -0.727957839 -0.789189844  1.408496661
ao_MLZ_40634     0.78496171 -0.036236989 -0.045856109 -1.330954745  1.294465304
ao_MLZ_40635    -0.60180903  0.237491925 -8.516340247 -1.922846051 -2.253167738
ao_MLZ_41497     0.74781607 -0.473739002  0.079702599 -0.541618659  0.851150321
ao_MLZ_45517     0.03668612  1.260227652 -3.029863934  5.540090501  4.714604883
ao_MLZ_48333     0.74543638 -0.268516721 -0.016018180 -0.524158366  0.921227978
ao_MLZ_50773     0.81835664  3.482899937  0.493462122  0.503753804 -0.914432825
ao_MLZ_50774     0.82493088  2.839349348  0.476266456  0.616170230 -1.118554654
ao_MLZ_50775     0.81102056  3.424254078  0.605525541  0.296404194 -1.023863567
ao_MLZ_59507     0.84170267 -0.803928522  0.272882996 -0.271897072  0.267076946
ao_MLZ_70063     0.75813237 -0.580764263  0.202198547  0.098177099  0.350607775
ao_MLZ_70074     0.78759477 -0.664157353  0.202950695 -0.564851061  0.483157316
ao_SP_1          0.83633999 -0.965616726  0.261515851 -0.471132125  0.416162883
ao_SP_2          0.86695312 -1.268115940  0.390787219 -0.259727809  0.114963244
ao_SP_3          0.86617505 -0.918436433  0.244749543 -0.066589477 -0.023540950
ao_SP_4          0.87467629 -0.841037959  0.291183003 -0.735091229  0.558067620
ao_SP_5          0.86160266 -0.913147701  0.408295241 -0.453847983  0.069343435
ao_SP_6          0.86167199 -0.706866154  0.368180059 -0.275451379  0.025042195
ao_SP_7          0.84212650 -1.386206075  0.373302536 -0.169327130  0.230446759
ao_SP_8          0.83699943 -1.228550842  0.280683842 -0.453188635  0.280629374
ao_SP_831        0.87506503 -1.321260390  0.331329731 -0.174026959 -0.067103877
ao_SP_832        0.86023731 -1.106354337  0.383697344 -0.315939988 -0.089359381
ao_SP_833        0.85881328 -0.995896235  0.311935843 -0.735878850  0.547594279
ao_SP_834        0.85426409 -1.255518350  0.336200356 -0.575183447  0.402780299
ao_SP_835        0.86993574 -1.367327862  0.453848173  0.003473097 -0.004526690
ao_SP_836        0.83700279 -1.549256191  0.314257220 -0.260600205 -0.003491483
ao_SP_837        0.82962230 -0.849038641  0.096349687 -0.054895256  0.390097831
ao_SP_838        0.80650660 -0.838626879  0.204563365 -0.196775623  0.284490436
ao_SP_839        0.87735574 -1.297797439  0.141642994 -0.327777370  0.536767477
ao_SP_840        0.87402902 -1.080041301  0.522224495 -0.238612528 -0.339190402
ao_UMMZ_103984   0.83760004 -0.449238620  0.154957009 -0.035657516  0.157517721
ao_UMMZ_130517   0.82557044  3.326226381  0.535390363  0.209198927 -0.790962211
ao_UMMZ_95618    0.82434785  3.480627608  0.154003549 -2.612850703  2.068945632
ao_UMMZ_95619    0.81086752  3.795181608  0.165648199 -2.635009684  2.216295291
                       PC6         PC7         PC8           PC9        PC10
ao_ANSP_90568  -0.01050292  0.02628323  0.08211367  0.0117706555  0.03089422
ao_BC_107       1.55814915 -0.61506709 -0.14042500  0.0799636544 -0.19933158
ao_BC_108       1.67012378 -0.81763651 -0.13996665 -0.2589126850 -0.18911946
ao_BC_109       1.28316909 -0.59590520 -0.12484364 -0.3935232969 -0.59357346
ao_BC_A112      0.29902390 -0.16919557  0.06791297 -0.0175518394 -0.17003307
ao_BC_A113      1.05711113 -1.52941586 -0.19796387 -0.4692079088 -1.19178213
ao_BC_A114      1.81278268 -0.33246698 -0.09418384  1.0232399341  1.01336646
ao_BC_A115      2.19919355 -0.36429135 -0.05711737  0.7405779208  1.42845619
ao_BC_A116      1.10498328 -0.63388521 -0.08683894  0.3624388455 -0.02318171
ao_BC_A117      0.86577243 -0.78598122 -0.10631730 -0.1970772908 -0.16775917
ao_BC_A118      0.99880240 -0.87785152 -0.20726044 -0.3471860765 -1.21654823
ao_LSUMZ_23890 -0.02746737 -0.07745958  6.13139542 -0.0955619017 -0.16745513
ao_LSUMZ_33050 -1.03329579 -0.39790339 -0.16634470 -0.3468451886  0.29605446
ao_LSUMZ_39731  0.13457978 -0.21866626 -0.16652834  0.5177663732  0.37428443
ao_LSUMZ_43831 -0.62677957  0.44833451 -0.12775624 -0.2276528403 -0.22770781
ao_LSUMZ_43832 -0.87730098  0.18834813 -0.15516481 -0.3924814780 -0.15597635
ao_MLZ_1105    -0.65003562 -0.15825692 -0.13353699 -0.3995051513 -0.43802912
ao_MLZ_32244    0.04140876  0.04904152 -0.21353084 -0.0003453247 -0.02076454
ao_MLZ_35920   -0.17772302 -0.36648028  0.48905463  0.0988795597  0.34497974
ao_MLZ_39530   -0.97560677 -1.52649956 -0.09939881  3.1253382046  1.33307320
ao_MLZ_40633   -1.23769671 -3.29217718 -0.23294694 -2.0769395146  2.34491022
ao_MLZ_40634   -0.92189498 -1.82257997 -0.12820030  0.3667183815 -1.01696852
ao_MLZ_40635   -0.28438108  0.60658228 -0.18097688 -0.1599358438 -0.13990583
ao_MLZ_41497   -1.25943488 -1.69295448 -0.17733865  0.0561313722 -0.65157407
ao_MLZ_45517    0.20075951  0.86662703 -0.31986464 -0.0579060616 -0.22388986
ao_MLZ_48333   -0.86123573 -1.40863086 -0.13663372  0.7115449596 -0.39905896
ao_MLZ_50773   -0.91340233  0.66785027  0.07926408 -0.1548726252  0.46021859
ao_MLZ_50774   -0.90429258  0.57821780 -0.11561550  0.1837989809 -0.08887032
ao_MLZ_50775   -0.96926167  0.08594994 -0.14743697  0.3026576954  0.16291873
ao_MLZ_59507   -0.10936027  0.47127108 -0.09774305  0.7579617235  1.08224294
ao_MLZ_70063   -0.97383277 -1.32493573 -0.18859320 -0.9464210955 -0.64900989
ao_MLZ_70074   -0.77004520 -0.85430847 -0.15820369  0.4146215554 -0.87050111
ao_SP_1        -0.49791559  0.79999931 -0.16408808 -0.0600052899 -0.24017065
ao_SP_2        -0.21282293  1.29439055 -0.07208273  0.1461014109  0.68953422
ao_SP_3         0.03812627  0.33995960 -0.12910122  0.6287352845  0.00633623
ao_SP_4        -0.32807531  1.36840357 -0.10807483  0.8004654993  0.03690431
ao_SP_5        -0.59418307  0.98697432 -0.04486160  0.2874505214  0.76749144
ao_SP_6        -0.25227227  0.84298871 -0.15507424 -0.1506021312  0.47063805
ao_SP_7        -0.04046810  0.98674084 -0.08464828 -2.1391517901  1.21012553
ao_SP_8        -0.20617946  0.44678632 -0.11950396  0.1722055602  0.36895680
ao_SP_831      -0.35400022  1.02163515 -0.16912124  0.0451742217 -0.73139263
ao_SP_832      -0.26932125  0.96115029 -0.11555935  0.0084221420 -0.31360719
ao_SP_833      -0.29669471  1.34620119 -0.10144954  0.6986142130 -0.18746862
ao_SP_834      -0.34393862  0.37804681 -0.18547251 -0.5564574068 -1.36433608
ao_SP_835       0.10712820  1.07145990 -0.07606744 -2.1852551080  1.34464437
ao_SP_836      -0.47727814  0.75639643 -0.23109032 -0.8668539795 -0.98804332
ao_SP_837      -0.37338530  0.48706846 -0.15938232  0.1064861686 -0.69495810
ao_SP_838      -0.20089133  0.17307729 -0.10722120  0.4249340787  0.30732142
ao_SP_839      -0.43446673  0.65849273 -0.14655529  0.3407636582 -0.78728130
ao_SP_840      -0.31843716  1.16506797 -0.11444962  0.0960035492  0.21162488
ao_UMMZ_103984 -0.01078903  0.35058443 -0.07478038  0.6556294496  0.46649415
ao_UMMZ_130517 -1.21783736  0.02178092 -0.12990109 -0.1602332922 -0.26636495
ao_UMMZ_95618   3.22451911  0.23091886 -0.12592099 -0.3434997331 -0.13620057
ao_UMMZ_95619   3.41687379  0.18591974 -0.13460323 -0.1604107199 -0.24060686
                       PC11        PC12         PC13         PC14         PC15
ao_ANSP_90568   0.024090221 -0.03102289 -0.017794045 -0.021308889 -0.047294257
ao_BC_107      -1.265345165 -0.42357870  0.897276000 -0.605233739 -0.321459046
ao_BC_108      -1.002458831 -0.43331445  0.641193504 -0.704713411 -0.227497784
ao_BC_109      -0.719939985 -0.27542328  0.656602639 -0.516559165 -0.099378938
ao_BC_A112      0.118854829 -0.11068992 -0.067473654 -0.587057065 -0.048793839
ao_BC_A113      0.990077665 -0.90051934 -0.601700860 -0.512664968 -0.202364393
ao_BC_A114     -0.462575418  0.86562614 -0.417248543  1.774694921  0.692966115
ao_BC_A115     -0.797731082  0.81683527  0.397831273  1.746340441  0.180447385
ao_BC_A116      0.063574596 -0.04973383 -0.165262201 -0.371950594 -0.170419829
ao_BC_A117      1.122335199  0.24157861 -0.799418722 -0.465842736 -0.327126059
ao_BC_A118      1.010560892 -0.97662162 -0.504239832 -0.573949712 -0.170883153
ao_LSUMZ_23890  0.061728967 -0.13672190 -0.044017893  0.116146957  0.151335331
ao_LSUMZ_33050  0.295705681 -0.32077298  0.419803877  0.309218353 -1.343414408
ao_LSUMZ_39731  1.318195388  2.00458909 -1.873868017 -1.140050119  1.839087350
ao_LSUMZ_43831 -0.505451853  0.27960348  0.336935047  0.054671770  1.293841090
ao_LSUMZ_43832 -0.347382210  0.05195721  0.849180204  0.690547877  0.822661191
ao_MLZ_1105    -0.312616523  0.20034830  0.529889124 -0.634202039  1.049456531
ao_MLZ_32244   -0.009471983  0.04072247 -0.013159960  0.003701096 -0.007578525
ao_MLZ_35920   -0.262688353  0.61839355  0.165691436 -0.472831694 -1.153625111
ao_MLZ_39530    1.870210531 -1.73039112  1.915150075 -0.560129465  1.022437559
ao_MLZ_40633   -1.367285318 -1.67158853 -1.625517042  0.016891034  0.584644294
ao_MLZ_40634   -1.157472961  1.89750886  0.694029393 -0.207576891  0.082540177
ao_MLZ_40635    0.092906961  0.22823204  0.036450934 -0.010054586 -0.082940692
ao_MLZ_41497    0.379092753  0.47741528 -0.170066951  0.398302243 -0.153768939
ao_MLZ_45517   -0.221592574 -0.37008616  0.402080353  0.283816334 -0.190745408
ao_MLZ_48333   -0.293464122  1.18034688  0.319634416 -0.365236339 -0.678720849
ao_MLZ_50773   -0.626846247 -0.05018631 -0.471930157 -0.470021837 -0.351940706
ao_MLZ_50774    0.073987778 -0.29681416 -0.090871574 -0.104125637  0.146390298
ao_MLZ_50775    0.099568554 -0.45156343 -0.075861627 -0.041542381 -0.621701461
ao_MLZ_59507    0.406961200 -0.20449426 -0.253598491 -0.199257615 -1.095572224
ao_MLZ_70063    0.978550690  1.29798988  0.681681824  0.716055304 -0.704254917
ao_MLZ_70074   -0.048479306  0.46775700  0.328950571  1.132804173  0.006211185
ao_SP_1         0.629070084 -0.28448454 -0.890525844  0.710872958  0.091821726
ao_SP_2         0.337663437  0.13325173 -0.421969054  0.163967127 -0.918914118
ao_SP_3         0.391288336  0.10263443 -0.162866075 -0.521851365 -0.346030554
ao_SP_4        -1.383576438 -0.20239671 -0.442877081 -1.131170877  0.034748487
ao_SP_5         0.096206811  0.10114349 -0.313008721  0.154995037 -0.870596437
ao_SP_6         0.510654414 -0.04266043 -0.273939822  0.587567036  0.374932498
ao_SP_7         0.842957822  0.79799297  1.346848754 -0.596089542  0.360624061
ao_SP_8        -0.116457204 -0.48041974  0.334762615  1.099243545 -0.829553217
ao_SP_831      -0.179261716 -0.15141181 -0.147693295 -0.850965151 -0.167389292
ao_SP_832      -0.430763856 -0.44655081  0.163157009 -0.324300750  0.267620330
ao_SP_833      -1.562995973 -0.26115925 -0.140516815 -0.753452873  0.237680514
ao_SP_834      -0.429978222 -0.77710070  0.477766702  0.890170690  1.494602740
ao_SP_835       0.987658071  0.75163388  1.431336715 -0.687792223  0.137178543
ao_SP_836       0.654516493 -1.18792572 -0.279456128  1.364104600  0.505693903
ao_SP_837       0.522701728  0.07631434 -1.286211484  0.535838320 -0.539125545
ao_SP_838      -0.277854973  0.35417372 -0.492042527  0.430261989 -0.296293417
ao_SP_839      -0.192385999 -0.26745981 -0.057601583  0.287535353  0.129840076
ao_SP_840       0.204464586 -0.41482417 -0.013417476  0.138150409  0.577771818
ao_UMMZ_103984 -0.479427066  0.53081198 -0.847771195 -0.547655875  0.498664200
ao_UMMZ_130517 -0.355737284 -0.21705519 -0.004648932  0.233704480 -0.482693974
ao_UMMZ_95618   0.359947753 -0.27076463 -0.072365968 -0.031683574 -0.088272539
ao_UMMZ_95619   0.365709225 -0.07912417  0.012689104  0.169669063 -0.044847770
                              pop      missing
ao_ANSP_90568            Yoro_Hon 0.9824503854
ao_BC_107                  Belize 0.0004920453
ao_BC_108                  Belize 0.0139412826
ao_BC_109                  Belize 0.0141052977
ao_BC_A112                 Belize 0.6327702149
ao_BC_A113                 Belize 0.0044284074
ao_BC_A114                 Belize 0.0013121207
ao_BC_A115                 Belize 0.0000000000
ao_BC_A116                 Belize 0.0018041660
ao_BC_A117                 Belize 0.0095128752
ao_BC_A118                 Belize 0.0009840905
ao_LSUMZ_23890         Tabasco_MX 0.9491553223
ao_LSUMZ_33050          Oaxaca_MX 0.0000000000
ao_LSUMZ_39731         Chiapas_MX 0.0008200754
ao_LSUMZ_43831          Colima_MX 0.0001640151
ao_LSUMZ_43832          Colima_MX 0.0024602263
ao_MLZ_1105          Socal_Parrot 0.0000000000
ao_MLZ_32244        Tamaulipas_MX 0.0226340823
ao_MLZ_35920          Veracruz_MX 0.0314908972
ao_MLZ_39530        Tamaulipas_MX 0.2402821060
ao_MLZ_40633        Tamaulipas_MX 0.1381007053
ao_MLZ_40634        Tamaulipas_MX 0.0008200754
ao_MLZ_40635        Tamaulipas_MX 0.7830080367
ao_MLZ_41497   San Luis Potosi_MX 0.0067246187
ao_MLZ_45517            Oaxaca_MX 0.1735279646
ao_MLZ_48333        Tamaulipas_MX 0.0044284074
ao_MLZ_50773          Guerrero_MX 0.0096768903
ao_MLZ_50774          Guerrero_MX 0.0036083320
ao_MLZ_50775          Guerrero_MX 0.0006560604
ao_MLZ_59507          Veracruz_MX 0.0106609808
ao_MLZ_70063         Socal_Parrot 0.0000000000
ao_MLZ_70074         Socal_Parrot 0.0000000000
ao_SP_1              Socal_Parrot 0.0001640151
ao_SP_2              Socal_Parrot 0.0001640151
ao_SP_3              Socal_Parrot 0.0001640151
ao_SP_4              Socal_Parrot 0.0000000000
ao_SP_5              Socal_Parrot 0.0000000000
ao_SP_6              Socal_Parrot 0.0004920453
ao_SP_7              Socal_Parrot 0.0000000000
ao_SP_8              Socal_Parrot 0.0001640151
ao_SP_831            Socal_Parrot 0.0000000000
ao_SP_832            Socal_Parrot 0.0001640151
ao_SP_833            Socal_Parrot 0.0000000000
ao_SP_834            Socal_Parrot 0.0000000000
ao_SP_835            Socal_Parrot 0.0000000000
ao_SP_836            Socal_Parrot 0.0000000000
ao_SP_837            Socal_Parrot 0.0000000000
ao_SP_838            Socal_Parrot 0.0000000000
ao_SP_839            Socal_Parrot 0.0000000000
ao_SP_840            Socal_Parrot 0.0000000000
ao_UMMZ_103984         Tabasco_MX 0.0000000000
ao_UMMZ_130517       Michoacan_MX 0.0009840905
ao_UMMZ_95618          Nayarit_MX 0.0001640151
ao_UMMZ_95619          Nayarit_MX 0.0000000000

Code

#outliers: Tamaulipas_MLZ_32244 appears to be contaminated above - removed
vcfR <- vcfR[, !colnames(vcfR@gt) %in% c("ao_MLZ_32244")]

#subset popmap to only include retained individuals
popmap<-popmap[popmap$id %in% colnames(vcfR@gt),]

#check missing data
miss<-missing_by_sample(vcfR)

No popmap provided

Code

vcfR.trim<-missing_by_sample(vcfR, cutoff = 0.80)

7 samples are above a 0.8 missing data cutoff, and were removed from VCF

Code

#check missing by SNP
missing_by_snp(vcfR.trim)

cutoff is not specified, exploratory visualizations will be generated

Warning in ggridges::geom_density_ridges(jittered_points = TRUE, position =
"raincloud", : Ignoring unknown parameters: `size`

Picking joint bandwidth of 0.0664

   filt missingness snps.retained
1  0.30  0.19337782         33894
2  0.50  0.13532357         29762
3  0.60  0.10760564         27383
4  0.65  0.09672365         26335
5  0.70  0.08159853         24701
6  0.75  0.07074896         23360
7  0.80  0.05888695         21717
8  0.85  0.03876374         18449
9  0.90  0.02595882         15914
10 0.95  0.01344531         12681
11 1.00  0.00000000          7084

Code

vcfR.trim.80<-missing_by_snp(vcfR.trim, cutoff = 0.8)

cutoff is specified, filtered vcfR object will be returned

62.17% of SNPs fell below a completeness cutoff of 0.8 and were removed from the VCF

Code

vcfR.trim.80

***** Object of Class vcfR *****
46 samples
26 CHROMs
21,717 variants
Object size: 27.2 Mb
5.889 percent missing data
*****        *****         *****

Code

#remove singletons
vcfR.trim.80<-min_mac(vcfR.trim.80, min.mac = 2)

89.53% of SNPs fell below a minor allele count of 2 and were removed from the VCF

Code

vcfR.trim.80

***** Object of Class vcfR *****
46 samples
26 CHROMs
2,274 variants
Object size: 4.3 Mb
7.746 percent missing data
*****        *****         *****

Code

# vcfR::write.vcf(vcfR.trim.80, "~/Dropbox/08_yhpa_072025/yhpa_final_filtered.vcf.gz")

Code

#labeled pca
#subset popmap to only include retained individuals
popmap<-popmap[popmap$id %in% colnames(vcfR.trim.80@gt),]

#convert each to genlight
gena<-vcfR2genlight(vcfR.trim.80)
#perform PCA
di.pca<-glPca(gena, nf=4)
#isolate PCA scores as a dataframe
di.pca.scores<-as.data.frame(di.pca$scores)
#reorder sampling file to match alphabetical order
popmap<-popmap %>% slice(order(factor(id, levels = rownames(di.pca.scores))))
#check that they all match
rownames(di.pca.scores) == popmap$id

 [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[16] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[31] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[46] TRUE

Code

#add in percent variance explained
var_frac <- di.pca$eig/sum(di.pca$eig)

#pca - Figure 1 (with map) - add numbered localities
ggplot(di.pca.scores, aes(x=PC1, y=PC2)) +
  geom_point(aes(fill=popmap$pop), pch=21, size=2) +
  ggrepel::geom_text_repel(aes(label = popmap$new_id)) +
  xlab(paste0("PC1, ", round(var_frac[1] * 100, 2), "% variance explained")) + 
  ylab(paste0("PC2, ", round(var_frac[2] * 100, 2), "% variance explained")) + 
  theme_classic()

Warning: ggrepel: 22 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Code

pop(gena)<-gena@ind.names
sample.div.80 <- stamppNeisD(gena, pop = FALSE)
plot(sample.div.80)

Code

#need to rename samples for splitstree
rownames(sample.div.80)

 [1] "ao_BC_107"      "ao_BC_108"      "ao_BC_109"      "ao_BC_A113"    
 [5] "ao_BC_A114"     "ao_BC_A115"     "ao_BC_A116"     "ao_BC_A117"    
 [9] "ao_BC_A118"     "ao_LSUMZ_33050" "ao_LSUMZ_39731" "ao_LSUMZ_43831"
[13] "ao_LSUMZ_43832" "ao_MLZ_1105"    "ao_MLZ_35920"   "ao_MLZ_40634"  
[17] "ao_MLZ_41497"   "ao_MLZ_48333"   "ao_MLZ_50773"   "ao_MLZ_50774"  
[21] "ao_MLZ_50775"   "ao_MLZ_59507"   "ao_MLZ_70063"   "ao_MLZ_70074"  
[25] "ao_SP_1"        "ao_SP_2"        "ao_SP_3"        "ao_SP_4"       
[29] "ao_SP_5"        "ao_SP_6"        "ao_SP_7"        "ao_SP_8"       
[33] "ao_SP_831"      "ao_SP_832"      "ao_SP_833"      "ao_SP_834"     
[37] "ao_SP_835"      "ao_SP_836"      "ao_SP_837"      "ao_SP_838"     
[41] "ao_SP_839"      "ao_SP_840"      "ao_UMMZ_103984" "ao_UMMZ_130517"
[45] "ao_UMMZ_95618"  "ao_UMMZ_95619"

Code

rownames(sample.div.80)<-gsub("ao_", "", rownames(sample.div.80))

#export for splitstree
stamppPhylip(distance.mat=sample.div.80, file="~/Dropbox/08_yhpa_072025/splitstree/oratrix.80.splitstree.txt")

knitr::include_graphics("~/Dropbox/08_yhpa_072025/splitstree/oratrix.80.splitstree.png")

Code

vcfR.trim.80

***** Object of Class vcfR *****
46 samples
26 CHROMs
2,274 variants
Object size: 4.3 Mb
7.746 percent missing data
*****        *****         *****

Code

miss<-missing_by_sample(vcfR.trim.80)

No popmap provided

Code

miss.df<-miss$unfiltered.stats
miss.df

                      samples prop.missing mean.depth
ao_BC_107           ao_BC_107 0.0312225154  18.815252
ao_BC_108           ao_BC_108 0.1873350923   9.719156
ao_BC_109           ao_BC_109 0.1816182938  10.306287
ao_BC_A113         ao_BC_A113 0.1015831135  11.771415
ao_BC_A114         ao_BC_A114 0.0452946350  16.698756
ao_BC_A115         ao_BC_A115 0.0329815303  19.201455
ao_BC_A116         ao_BC_A116 0.0901495163  11.386660
ao_BC_A117         ao_BC_A117 0.1644678980   9.177895
ao_BC_A118         ao_BC_A118 0.0426561126  16.884704
ao_LSUMZ_33050 ao_LSUMZ_33050 0.0237467018  73.957207
ao_LSUMZ_39731 ao_LSUMZ_39731 0.0206684257  55.024248
ao_LSUMZ_43831 ao_LSUMZ_43831 0.1627088830  40.151261
ao_LSUMZ_43832 ao_LSUMZ_43832 0.1701846966  24.487546
ao_MLZ_1105       ao_MLZ_1105 0.0004397537 127.820062
ao_MLZ_35920     ao_MLZ_35920 0.5369393140   9.587844
ao_MLZ_40634     ao_MLZ_40634 0.0307827617  24.389292
ao_MLZ_41497     ao_MLZ_41497 0.2145998241  14.923852
ao_MLZ_48333     ao_MLZ_48333 0.2471416007  15.459112
ao_MLZ_50773     ao_MLZ_50773 0.3117854002  14.190415
ao_MLZ_50774     ao_MLZ_50774 0.2409850484  20.018540
ao_MLZ_50775     ao_MLZ_50775 0.0325417766  32.662273
ao_MLZ_59507     ao_MLZ_59507 0.4670184697  12.890264
ao_MLZ_70063     ao_MLZ_70063 0.0008795075  95.510563
ao_MLZ_70074     ao_MLZ_70074 0.0000000000 199.379068
ao_SP_1               ao_SP_1 0.0325417766  20.227727
ao_SP_2               ao_SP_2 0.0167106420  24.490161
ao_SP_3               ao_SP_3 0.0123131047  25.924310
ao_SP_4               ao_SP_4 0.0092348285  33.585442
ao_SP_5               ao_SP_5 0.0233069481  21.771274
ao_SP_6               ao_SP_6 0.0136323659  24.906821
ao_SP_7               ao_SP_7 0.0039577836  41.710375
ao_SP_8               ao_SP_8 0.0101143360  31.190582
ao_SP_831           ao_SP_831 0.0035180299  44.871580
ao_SP_832           ao_SP_832 0.0092348285  40.393697
ao_SP_833           ao_SP_833 0.0061565523  39.670796
ao_SP_834           ao_SP_834 0.0048372911  44.629695
ao_SP_835           ao_SP_835 0.0039577836  43.298896
ao_SP_836           ao_SP_836 0.0030782762  47.913101
ao_SP_837           ao_SP_837 0.0013192612  57.015852
ao_SP_838           ao_SP_838 0.0043975374  38.384717
ao_SP_839           ao_SP_839 0.0074758135  35.198051
ao_SP_840           ao_SP_840 0.0021987687  47.413398
ao_UMMZ_103984 ao_UMMZ_103984 0.0101143360  93.946690
ao_UMMZ_130517 ao_UMMZ_130517 0.0312225154  31.886972
ao_UMMZ_95618   ao_UMMZ_95618 0.0083553210  65.929047
ao_UMMZ_95619   ao_UMMZ_95619 0.0079155673  93.606383

Code

# write.csv(miss.df, "~/Dropbox/08_yhpa_072025/yhpa_final_filtered_stats.csv")

Code

#thinning final vcf for Locator analysis
vcfR.trim.80.thin<-distance_thin(vcfR.trim.80, min.distance = 10000)


  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |===                                                                   |   4%
  |                                                                            
  |=====                                                                 |   8%
  |                                                                            
  |========                                                              |  12%
  |                                                                            
  |===========                                                           |  15%
  |                                                                            
  |=============                                                         |  19%
  |                                                                            
  |================                                                      |  23%
  |                                                                            
  |===================                                                   |  27%
  |                                                                            
  |======================                                                |  31%
  |                                                                            
  |========================                                              |  35%
  |                                                                            
  |===========================                                           |  38%
  |                                                                            
  |==============================                                        |  42%
  |                                                                            
  |================================                                      |  46%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================                                |  54%
  |                                                                            
  |========================================                              |  58%
  |                                                                            
  |===========================================                           |  62%
  |                                                                            
  |==============================================                        |  65%
  |                                                                            
  |================================================                      |  69%
  |                                                                            
  |===================================================                   |  73%
  |                                                                            
  |======================================================                |  77%
  |                                                                            
  |=========================================================             |  81%
  |                                                                            
  |===========================================================           |  85%
  |                                                                            
  |==============================================================        |  88%
  |                                                                            
  |=================================================================     |  92%
  |                                                                            
  |===================================================================   |  96%
  |                                                                            
  |======================================================================| 100%

1460 out of 2274 input SNPs were not located within 10000 base-pairs of another SNP and were retained despite filtering

Code

vcfR.trim.80.thin

***** Object of Class vcfR *****
46 samples
26 CHROMs
1,460 variants
Object size: 2.9 Mb
8.03 percent missing data
*****        *****         *****

Code

# vcfR::write.vcf(vcfR.trim.80.thin, "~/Dropbox/08_yhpa_072025/yhpa_final_filtered_unlinked.vcf.gz")