envGWAS_850K

workflowr

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Last updated: 2021-06-08

Checks: 7 0

Knit directory: local_adaptation_sequence/

This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

---

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Ignored files:
    Ignored:    .DS_Store
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/.DS_Store
    Ignored:    data/Bos_taurus.ARS-UCD1.2.103.gtf.gz
    Ignored:    data/Bos_taurus.ARS-UCD1.2.QTL.gff.gz
    Ignored:    data/FAANG_peaks.bed.gz
    Ignored:    output/.DS_Store
    Ignored:    output/200910_RAN/.DS_Store
    Ignored:    output/200910_RAN/genes/
    Ignored:    output/200910_RAN/gwas/
    Ignored:    output/200910_RAN/seq_gwas/
    Ignored:    output/200910_RAN/sfs_selection/
    Ignored:    output/selscan_window/200907_SIM.all.nsl.out.100bins.norm.windows.txt
    Ignored:    output/selscan_window/200907_SIM.all.nsl.windows.txt
    Ignored:    output/selscan_window/200907_SIM.oldest_5000.nsl.out.100bins.norm.gz
    Ignored:    output/selscan_window/200907_SIM.purebred.nsl.out.100bins.norm.gz
    Ignored:    output/selscan_window/200907_SIM.purebred.nsl.out.100bins.norm.windows.txt
    Ignored:    output/selscan_window/200907_SIM.purebred.nsl.windows.txt
    Ignored:    output/selscan_window/200907_SIM.somesim.nsl.out.100bins.norm.gz
    Ignored:    output/selscan_window/200907_SIM.somesim.nsl.windows.txt
    Ignored:    output/selscan_window/200907_SIM.young_5000.nsl.out.100bins.norm.gz
    Ignored:    output/selscan_window/200910_RAN.all.nsl.out.100bins.norm.gz
    Ignored:    output/selscan_window/200910_RAN.all.nsl.out.100bins.norm.windows.txt
    Ignored:    output/selscan_window/200910_RAN.all.nsl.windows.txt
    Ignored:    output/selscan_window/200910_RAN.oldest_5000.nsl.out.100bins.norm.gz
    Ignored:    output/selscan_window/200910_RAN.young_5000.nsl.out.100bins.norm.gz

Untracked files:
    Untracked:  analysis/test.Rmd
    Untracked:  output/200907_SIM/
    Untracked:  output/200910_RAN/af_trajectories/
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---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/envGWAS_850K.Rmd) and HTML (docs/envGWAS_850K.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
Rmd	a019901	Troy Rowan	2021-06-08	Red angus corrections
html	f56f685	Troy Rowan	2021-06-08	Build site.
Rmd	77e94f5	Troy Rowan	2021-06-08	Updated with 850K envGWAS analysis
Rmd	63f88e5	Troy Rowan	2021-05-13	Added envGWAS preliminary analysis

---

source("code/GCTA_functions.R")
source("code/annotation_functions.R")

Simmental

850K envGWAS

Manhattan plots with both p and q values

sim_manhattans = 
  unique(sim_envgwas$variable) %>%
    purrr::map(~plot_grid(ggmanhattan2(filter(sim_envgwas, variable == .x & p < 0.1), pcol = p, value = p) + ggtitle(.x),
                          ggmanhattan2(filter(sim_envgwas, variable == .x & p < 0.1), pcol = q, value = q),
                          nrow = 2))

envGWAS Runs

AridPrairie

sim_manhattans[[1]]

Past versions of unnamed-chunk-4-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

CornBelt

sim_manhattans[[2]]

Past versions of unnamed-chunk-5-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Desert

sim_manhattans[[3]]

Past versions of unnamed-chunk-6-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

dewpoint

sim_manhattans[[4]]

Past versions of unnamed-chunk-7-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

elev

sim_manhattans[[5]]

Past versions of unnamed-chunk-8-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

FescueBelt

sim_manhattans[[6]]

Past versions of unnamed-chunk-9-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Foothills

sim_manhattans[[7]]

Past versions of unnamed-chunk-10-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

ForestedMountains

sim_manhattans[[8]]

Past versions of unnamed-chunk-11-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

HighPlains

sim_manhattans[[9]]

Past versions of unnamed-chunk-12-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

latitude

sim_manhattans[[10]]

Past versions of unnamed-chunk-13-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

longitude

sim_manhattans[[11]]

Past versions of unnamed-chunk-14-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

maxtemp

sim_manhattans[[12]]

Past versions of unnamed-chunk-15-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

maxvap

sim_manhattans[[13]]

Past versions of unnamed-chunk-16-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

meantemp

sim_manhattans[[14]]

Past versions of unnamed-chunk-17-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

mintemp

sim_manhattans[[15]]

Past versions of unnamed-chunk-18-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

minvap

sim_manhattans[[16]]

Past versions of unnamed-chunk-19-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

precip

sim_manhattans[[17]]

Past versions of unnamed-chunk-20-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Southeast

sim_manhattans[[18]]

Past versions of unnamed-chunk-21-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

UpperMidwest

sim_manhattans[[19]]

Past versions of unnamed-chunk-22-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

# cat('# # Simmental 850K envGWAS {.tabset}   \n')
# invisible(
#   sim_envgwas %>% 
#       dplyr::group_split(variable) %>% 
#       purrr::imap(.,~{
#         # create tabset for each group 
#         cat('### Tab',.y,'   \n')
#         cat('\n')
#         #p <- ggmanhattan2(filter(.x, p < 0.1), sigsnps = sim_multisig)
#         p <- filter(.x, p < 0.1) %>% ggplot(aes(CHR, BP))+geom_point()
#         cat(as.character(htmltools::tagList(p)))
#       })
# )

Number of significant SNPs in each analysis at 850K level

Number of SNPs in each analysis that reaches genome-wide significance at 1) Bonferroni 2) p < 1e-5 3) q < 0.1

sim_envgwas %>% 
  group_by(variable) %>% 
  summarize(bonfCount = sum(p < 6e-8),
            pCount = sum(p < 1e-5),
            qCount = sum(q < 0.1))

# A tibble: 19 x 4
   variable          bonfCount pCount qCount
   <chr>                 <int>  <int>  <int>
 1 AridPrairie               0     29     11
 2 CornBelt                  0     16      3
 3 Desert                   26    158    334
 4 dewpoint                  1      8      3
 5 elev                      1     14      3
 6 FescueBelt                0     11      0
 7 Foothills                 4     43     16
 8 ForestedMountains         1     13      3
 9 HighPlains                0     16      6
10 latitude                  1     10      1
11 longitude                 1     23      5
12 maxtemp                   0     10      2
13 maxvap                    0     11      0
14 meantemp                  1      8      2
15 mintemp                   1      9      2
16 minvap                    1     27      1
17 precip                    5     14      7
18 Southeast                 0     15      0
19 UpperMidwest              0     10      0

Number of SNPs that are shared across zones/variables

filter(sim_envgwas, p < 1e-5) %>%
  count(SNP, sort = TRUE)%>%
  filter(n>1) %>%
  kbl() %>%
  kable_styling()

SNP	n
25:40171577:C:T	10
23:11653102:T:G	6
18:58490610:T:G	5
22:24449349:A:G	5
28:37890881:G:A	5
28:37891750:A:C	5
16:42569828:C:T	4
17:72089995:A:G	4
6:45760951:A:G	4
19:59908502:C:T	3
22:46620047:A:G	3
28:37892541:G:A	3
4:84863571:A:G	3
1:102180787:T:C	2
1:116110811:T:C	2
1:153515980:C:T	2
15:17921054:T:C	2
2:72751717:T:C	2
2:97342131:G:A	2
20:8095171:T:C	2
21:11109237:C:T	2
23:1747454:A:C	2
5:21848046:C:T	2
5:83441154:A:C	2

Red Angus

850K envGWAS

ran_envgwas =
  # list.files("output/200910_RAN/gwas") %>%
  #   map(
  #     ~read_gwas2(paste0("output/200910_RAN/gwas/", .x)) %>%
  #       mutate(variable = .x)) %>%
  #   reduce(bind_rows) %>%
  # mutate(variable = str_replace(variable, pattern = "200910_RAN.", ""),
  #        variable = str_replace(variable, pattern = ".850K.mlma.gz", ""),
  #        variable = str_replace(variable, pattern = "_noLSF", ""))

#write_csv(ran_envgwas, "output/200910_RAN/gwas/200910_RAN.AllGWAS.850K.mlma.gz")
  read_csv("output/200910_RAN/gwas/200910_RAN.AllGWAS.850K.mlma.gz",
           col_types = cols(SNP = col_character(), chrbp = col_character())) %>%
  filter(CHR < 30)

ran_multisig =
  filter(ran_envgwas, p < 1e-5) %>%
  count(SNP, sort = TRUE)%>%
  filter(n>1) %>%
  .$SNP

ran_manhattans = 
  unique(ran_envgwas$variable) %>%
    purrr::map(~plot_grid(ggmanhattan2(filter(ran_envgwas, variable == .x & p < 0.1),pcol = p)+
                 ggtitle(.x),
                          ggmanhattan2(filter(ran_envgwas, variable == .x & p < 0.1),pcol = p),
                          nrow = 2))

envGWAS Runs

AridPrairie

ran_manhattans[[1]]

Past versions of unnamed-chunk-27-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

CornBelt

ran_manhattans[[2]]

Past versions of unnamed-chunk-28-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Desert

ran_manhattans[[3]]

Past versions of unnamed-chunk-29-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

dewpoint

ran_manhattans[[4]]

Past versions of unnamed-chunk-30-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

elev

ran_manhattans[[5]]

Past versions of unnamed-chunk-31-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

FescueBelt

ran_manhattans[[6]]

Past versions of unnamed-chunk-32-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Foothills

ran_manhattans[[7]]

Past versions of unnamed-chunk-33-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

ForestedMountains

ran_manhattans[[8]]

Past versions of unnamed-chunk-34-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

HighPlains

ran_manhattans[[9]]

Past versions of unnamed-chunk-35-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

latitude

ran_manhattans[[10]]

Past versions of unnamed-chunk-36-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

longitude

ran_manhattans[[11]]

Past versions of unnamed-chunk-37-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

maxtemp

ran_manhattans[[12]]

Past versions of unnamed-chunk-38-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

maxvap

ran_manhattans[[13]]

Past versions of unnamed-chunk-39-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

meantemp

ran_manhattans[[14]]

Past versions of unnamed-chunk-40-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

mintemp

ran_manhattans[[15]]

Past versions of unnamed-chunk-41-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

minvap

ran_manhattans[[16]]

Past versions of unnamed-chunk-42-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

precip

ran_manhattans[[17]]

Past versions of unnamed-chunk-43-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Southeast

ran_manhattans[[18]]

Past versions of unnamed-chunk-44-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

UpperMidwest

ran_manhattans[[19]]

Past versions of unnamed-chunk-45-1.png

Version	Author	Date
f56f685	Troy Rowan	2021-06-08

Annotating Genes

Skipping for now

Number of significant SNPs in each analysis at 850K level

Number of SNPs in each analysis that reaches genome-wide significance at 1) Bonferroni 2) p < 1e-5 3) q < 0.1

ran_envgwas %>% 
  group_by(variable) %>% 
  summarize(bonfCount = sum(p < 6e-8),
            pCount = sum(p < 1e-5),
            qCount = sum(q < 0.1))

# A tibble: 19 x 4
   variable          bonfCount pCount qCount
   <chr>                 <int>  <int>  <int>
 1 AridPrairie               0      9     11
 2 CornBelt                  0     16     16
 3 Desert                  186    533   1612
 4 dewpoint                  0      8    151
 5 elev                      0     14     81
 6 FescueBelt                1     12      6
 7 Foothills                 4     44    109
 8 ForestedMountains        22     53    181
 9 HighPlains                1     10     34
10 latitude                  0      9    167
11 longitude                 7     31    106
12 maxtemp                   3     14    148
13 maxvap                    2     11    119
14 meantemp                  2     10    167
15 mintemp                   0     12    175
16 minvap                    2     13      8
17 precip                    0     14     60
18 Southeast                 4     23    105
19 UpperMidwest              4     19     94

Number of SNPs that are shared across zones/variables

At p < 1e-5 threshold

filter(ran_envgwas, p < 1e-5) %>%
  count(SNP, sort = TRUE)%>%
  filter(n>1) %>%
  kbl() %>%
  kable_styling()

SNP	n
5:56294803:C:T	8
6:89632622:C:T	8
11:66022330:T:C	5
16:31189754:C:T	5
26:22147551:A:G	5
5:55940985:C:A	4
5:99932542:A:C	4
15:63936462:G:A	3
23:1760296:G:A	3
23:1762985:C:T	3
23:1764305:C:T	3
23:1765645:C:T	3
23:1768070:C:T	3
23:1773893:A:G	3
23:1780836:T:C	3
4:15143313:T:C	3
5:29337648:C:T	3
5:99970391:T:C	3
13:11805638:G:A	2
15:63923159:C:T	2
15:63930524:T:C	2
18:1421130:A:G	2
18:55917363:G:A	2
18:55918169:C:G	2
18:55923037:C:T	2
2:76462949:C:A	2
23:1741368:T:C	2
23:1742961:G:A	2
23:1744435:G:A	2
23:1745568:C:T	2
23:1747454:A:C	2
23:1750999:G:T	2
23:1753411:C:A	2
23:1755721:T:C	2
29:44876613:A:G	2
4:114194176:G:A	2
4:117086624:G:A	2
5:34082134:C:T	2
5:83684035:C:T	2
6:83637243:A:G	2

Session information

sessionInfo()

R version 4.0.4 (2021-02-15)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] viridis_0.5.1     viridisLite_0.3.0 kableExtra_1.3.4  UpSetR_1.4.0     
 [5] DT_0.17           gprofiler2_0.2.0  cowplot_1.1.1     GALLO_1.1        
 [9] qvalue_2.22.0     pedigree_1.4      reshape_0.8.8     HaploSim_1.8.4   
[13] Matrix_1.3-2      lubridate_1.7.10  forcats_0.5.1     stringr_1.4.0    
[17] dplyr_1.0.5       readr_1.4.0       tidyr_1.1.3       tibble_3.1.0     
[21] tidyverse_1.3.0   here_1.0.1        ggcorrplot_0.1.3  corrr_0.4.3      
[25] factoextra_1.0.7  ggplot2_3.3.3     purrr_0.3.4       ggthemes_4.2.4   
[29] maps_3.3.0        knitr_1.31        workflowr_1.6.2  

loaded via a namespace (and not attached):
  [1] colorspace_2.0-0            ellipsis_0.3.1             
  [3] rprojroot_2.0.2             circlize_0.4.12            
  [5] XVector_0.30.0              GenomicRanges_1.42.0       
  [7] GlobalOptions_0.1.2         fs_1.5.0                   
  [9] rstudioapi_0.13             farver_2.1.0               
 [11] ggrepel_0.9.1               fansi_0.4.2                
 [13] xml2_1.3.2                  codetools_0.2-18           
 [15] splines_4.0.4               doParallel_1.0.16          
 [17] jsonlite_1.7.2              Rsamtools_2.6.0            
 [19] broom_0.7.5                 dbplyr_2.1.0               
 [21] compiler_4.0.4              httr_1.4.2                 
 [23] backports_1.2.1             assertthat_0.2.1           
 [25] lazyeval_0.2.2              cli_2.3.1                  
 [27] later_1.1.0.1               htmltools_0.5.1.1          
 [29] tools_4.0.4                 GenomeInfoDbData_1.2.4     
 [31] gtable_0.3.0                glue_1.4.2                 
 [33] reshape2_1.4.4              Rcpp_1.0.6                 
 [35] Biobase_2.50.0              cellranger_1.1.0           
 [37] Biostrings_2.58.0           vctrs_0.3.6                
 [39] svglite_2.0.0               rtracklayer_1.50.0         
 [41] iterators_1.0.13            xfun_0.22                  
 [43] rvest_1.0.0                 lifecycle_1.0.0            
 [45] XML_3.99-0.6                zlibbioc_1.36.0            
 [47] scales_1.1.1                MatrixGenerics_1.2.1       
 [49] hms_1.0.0                   promises_1.2.0.1           
 [51] SummarizedExperiment_1.20.0 parallel_4.0.4             
 [53] RColorBrewer_1.1-2          yaml_2.2.1                 
 [55] gridExtra_2.3               stringi_1.5.3              
 [57] highr_0.8                   unbalhaar_2.0              
 [59] S4Vectors_0.28.1            foreach_1.5.1              
 [61] BiocGenerics_0.36.1         BiocParallel_1.24.1        
 [63] shape_1.4.5                 GenomeInfoDb_1.26.7        
 [65] matrixStats_0.58.0          rlang_0.4.10               
 [67] pkgconfig_2.0.3             systemfonts_1.0.1          
 [69] bitops_1.0-6                evaluate_0.14              
 [71] lattice_0.20-41             labeling_0.4.2             
 [73] GenomicAlignments_1.26.0    htmlwidgets_1.5.3          
 [75] tidyselect_1.1.0            plyr_1.8.6                 
 [77] magrittr_2.0.1              R6_2.5.0                   
 [79] IRanges_2.24.1              generics_0.1.0             
 [81] DelayedArray_0.16.3         DBI_1.1.1                  
 [83] pillar_1.5.1                haven_2.3.1                
 [85] whisker_0.4                 withr_2.4.1                
 [87] RCurl_1.98-1.3              modelr_0.1.8               
 [89] crayon_1.4.1                utf8_1.2.1                 
 [91] plotly_4.9.3                rmarkdown_2.7              
 [93] grid_4.0.4                  readxl_1.3.1               
 [95] data.table_1.14.0           git2r_0.28.0               
 [97] reprex_1.0.0                digest_0.6.27              
 [99] webshot_0.5.2               httpuv_1.5.5               
[101] stats4_4.0.4                munsell_0.5.0