Imputation of Latin American Cassava

workflowr

• Summary
• Checks
• Past versions

Last updated: 2020-08-26

Checks: 7 0

Knit directory: EMBRAPA_2020GS/

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.

---

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20200826)

The command set.seed(20200826) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: bcd83b4

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version bcd83b4. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:

Ignored files:
    Ignored:    .DS_Store
    Ignored:    .Rproj.user/
    Ignored:    analysis/.DS_Store
    Ignored:    data/.DS_Store

Untracked files:
    Untracked:  data/Report-DCas20-5360/

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/Imputation_EMBRAPA_102419.Rmd) and HTML (docs/Imputation_EMBRAPA_102419.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	9d4dfab	wolfemd	2020-08-26	Code organized into functions. Ready to run imputation of C2?

---

Solanine –> cbsurobbins

scp -r ~/embrapa_dataset mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/

Rename (on cbsurobbins hereon)

mv /workdir/marnin/embrapa_dataset /workdir/marnin/embrapa_dataset_102419

Destination folder for results

mkdir /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419

paste0("/workdir/marnin/nextgenImputation2019/",
       "DCas19_4301_DArTseqLD_AllSites_AllChrom_raw_70919.vcf.gz")

/workdir/marnin/EMBRAPA/TrainPopSamplesWithGBSplusDArT_80718.txt /workdir/marnin/EMBRAPA/TrainPopSamplesWithGBSonly_80718.txt

Prepare samples with GBS+DArT

Sample Lists

IBDmatches<-readRDS(file=paste0("/workdir/marnin/nextgenImputation2019/VerifyByIBD_EMBRAPA_102419/",
                                "gbs2dart_SamplesVerifiedByIBD_102419.rds"))

samplesWithVerifiedGBSandDart<-IBDmatches$NameGBS
write.table(samplesWithVerifiedGBSandDart,
            file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                        "samplesWithVerifiedGBSandDart_102419.txt"), 
            row.names = F, col.names = F, quote = F)  
dartNames_samplesWithVerifiedGBSandDart<-IBDmatches$NameDArT
write.table(dartNames_samplesWithVerifiedGBSandDart,
            file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                        "dartNames_samplesWithVerifiedGBSandDart_102419.txt"), 
            row.names = F, col.names = F, quote = F)  

Site+Allele Lists

library(tidyverse); library(magrittr); library(furrr); plan(multiprocess); options(mc.cores=18)

embrapa_dataset_sites<-tibble(Chr=1:18) %>% 
  mutate(SiteWithAlleles=future_map(Chr,function(Chr){ 
    sites<-read.table(file = paste0("/workdir/marnin/embrapa_dataset_102419/tassel_embrapa_newfastq_filter/",
                                    "tassel_embrapa_newfastq.chr",Chr,".bial.recode.sitesWithAlleles"),
                      stringsAsFactors = F, header = F) }))

dart_sites<-read.table(paste0("/workdir/marnin/nextgenImputation2019/",
                              "DCas19_4301_DArTseqLD_AllSites_AllChrom_raw_70919.sitesWithAlleles"),
                       stringsAsFactors = F, header = T)

# GBS-unique sites
gbs_unique_sites<-embrapa_dataset_sites %>% # GBS sites
    unnest(SiteWithAlleles) %>% 
    rename(CHROM=V1,
         POS=V2,
         ID=V3,
         REF=V4,
         ALT=V5) %>% 
  anti_join(dart_sites) %>%  # that are unique (not in the dart report 4301)
  select(CHROM,POS) %>% arrange(CHROM,POS); nrow(gbs_unique_sites) # 398327 
                 ## it's alot because we are starting from unimputed GBS data
write.table(gbs_unique_sites,
            file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                        "gbs_unique_sites_102419.txt"), 
            row.names = F, col.names = F, quote = F) 

Extract from raw VCF

library(tidyverse); library(magrittr); require(furrr); options(mc.cores=18); plan(multiprocess)
tibble(Chr=1:18) %>%
  mutate(ExtractRaw_gbsSamples=future_map(Chr,function(Chr){
    system(paste0("vcftools --gzvcf /workdir/marnin/embrapa_dataset_102419/tassel_embrapa_newfastq_filter/",
                  "tassel_embrapa_newfastq.chr",Chr,".bial.recode.vcf.gz ",
                  "--keep /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "samplesWithVerifiedGBSandDart_102419.txt ",
                  "--chr ",Chr," ",
                  "--positions /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "gbs_unique_sites_102419.txt ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromGBS_gbsUniqueSites_unfiltered_102419.vcf.gz")) }))

Extract from DCas19_4301

tibble(Chr=1:18) %>%
  mutate(ExtractRaw_dartSamples=future_map(Chr,function(Chr){
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/",
                               "DCas19_4301_DArTseqLD_AllSites_AllChrom_raw_70919.vcf.gz ",
                  "--keep /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "dartNames_samplesWithVerifiedGBSandDart_102419.txt ",
                  "--chr ",Chr," ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_102419.vcf.gz")) }))

system(paste0("bcftools query --list-samples /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
              "chr1_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_102419.vcf.gz ",
              "> /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
              "sampleNamesInOrder_samplesWithGBSandDArT_FromDArT_102419.txt")) 

dart_sampleNamesInOrder<-read.table(paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "sampleNamesInOrder_samplesWithGBSandDArT_FromDArT_102419.txt"), 
           stringsAsFactors = F, header = F)
dart_sampleNamesInOrder %>%
  rename(NameDArT=V1) %>% 
  mutate(Order=1:nrow(.)) %>% 
  left_join(IBDmatches) %$% NameGBS %>% 
  write.table(.,
            file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                        "gbsNames_InOrder_forRenamingDartSamples_102419.txt"), 
            row.names = F, col.names = F, quote = F) 

Rename extracted DArT VCF to match GBS

tibble(Chr=1:18) %>%
  mutate(Index=future_map(Chr,function(Chr){ 
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_102419.vcf.gz"))
    }))
tibble(Chr=1:18) %>%
  mutate(Header=future_map(Chr,function(Chr){ 
    system(paste0("tabix --print-header -f /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_102419.vcf.gz ",
                  "> /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_102419.header"))
    }))
tibble(Chr=1:18) %>%
  mutate(ReNameVCF=future_map(Chr,function(Chr){
    system(paste0("bcftools reheader --samples /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "gbsNames_InOrder_forRenamingDartSamples_102419.txt ",
                  "--output /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_renamed_102419.vcf.gz ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_102419.vcf.gz"))
    }))

Index everything

tibble(Chr=1:18) %>%
  mutate(Index=future_map(Chr,function(Chr){ 
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromGBS_gbsUniqueSites_unfiltered_102419.vcf.gz"))
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_renamed_102419.vcf.gz"))
    }))

Reorder DArT and GBS files to match

system(paste0("bcftools query --list-samples /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
              "chr1_samplesWithGBSandDArT_FromGBS_gbsUniqueSites_unfiltered_102419.vcf.gz ",
              "> /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
              "sampleNamesInOrder_samplesWithGBSandDArT_FromGBS_gbsUniqueSites_unfiltered_102419.txt"))

tibble(Chr=1:18) %>%
  mutate(Sort=future_map(Chr,function(Chr){ 
    system(paste0("bcftools view --samples-file ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "sampleNamesInOrder_samplesWithGBSandDArT_FromGBS_gbsUniqueSites_unfiltered_102419.txt ",
                  "--output-type z --output-file ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_sorted_102419.vcf.gz ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_renamed_102419.vcf.gz"))}))

tibble(Chr=1:18) %>%
  mutate(Index=future_map(Chr,function(Chr){ 
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_sorted_102419.vcf.gz")) }))

Concat DArT and GBS

tibble(Chr=1:18) %>%
  mutate(Concat=future_map(Chr,function(Chr){ 
    system(paste0("bcftools concat --allow-overlaps ",
                  "--output /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.vcf.gz ",
                  "--output-type z --threads 6 ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSandDArT_FromDArT_dartUniquePlusIntersectingSites_unfiltered_sorted_102419.vcf.gz ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSandDArT_FromGBS_gbsUniqueSites_unfiltered_102419.vcf.gz"))}))

Prepare samples with GBS-only

Extract from raw VCF

tibble(Chr=1:18) %>%
  mutate(ExtractRaw_gbsOnlySamples=future_map(Chr,function(Chr){
    system(paste0("vcftools --gzvcf /workdir/marnin/embrapa_dataset_102419/tassel_embrapa_newfastq_filter/",
                  "tassel_embrapa_newfastq.chr",Chr,".bial.recode.vcf.gz ",
                  "--remove /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/",
                  "samplesWithVerifiedGBSandDart_102419.txt ",
                  "--chr ",Chr," ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.vcf.gz")) }))

Prepare samples from DCas19_4403

See convertDCas19_4403_ToVCF_102419.Rmd

tibble(Chr=1:18) %>%
  mutate(ExtractRaw_dartPerChrom=future_map(Chr,function(Chr){
    system(paste0("vcftools --gzvcf /workdir/marnin/DCas19_4403/DCas19_4403_102419.vcf.gz ",
                  "--chr ",Chr," ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_102419.vcf.gz"))}))

Merge VCFs to form panel to be imputed

Index

tibble(Chr=1:18) %>%
  mutate(Index=future_map(Chr,function(Chr){ 
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.vcf.gz"))
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.vcf.gz"))
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_102419.vcf.gz"))
    }))
#system(paste0("tabix -f -p vcf /workdir/marnin/DCas19_4403/DCas19_4403_102419.vcf.gz"))

… merge step had problems…. duplicate sites in one of the files!?

Site+Allele Lists

library(tidyverse); library(magrittr); library(furrr); options(mc.cores=18); plan(multiprocess)
tibble(Chr=1:18) %>%
  mutate(SiteWithAlleles=future_map(Chr,function(Chr){ 
    system(paste0("zcat /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.vcf.gz ",
                  "| cut -f1-5 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.sitesWithAlleles"))

    system(paste0("zcat /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.vcf.gz ",
                  "| cut -f1-5 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.sitesWithAlleles"))
  
        system(paste0("zcat /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_102419.vcf.gz ",
                  "| cut -f1-5 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_102419.sitesWithAlleles"))
    }))

site_lists<-tibble(Chr=1:18) %>% 
  mutate(samplesWithGBSandDArT=future_map(Chr,function(Chr){ 
    sites<-read.table(file = paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                                    Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.sitesWithAlleles"),
                      stringsAsFactors = F, header = F) }),
    samplesWithGBSonly=future_map(Chr,function(Chr){ 
    sites<-read.table(file = paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                                    Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.sitesWithAlleles"),
                      stringsAsFactors = F, header = F) }),
    dcas19_4403=future_map(Chr,function(Chr){ 
    sites<-read.table(file = paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                                    Chr,"_DCas19_4403_102419.sitesWithAlleles"),
                      stringsAsFactors = F, header = F) }))

site_lists %<>%
  mutate(samplesWithGBSandDArT=map(samplesWithGBSandDArT,function(samplesWithGBSandDArT){
    samplesWithGBSandDArT %>% 
      semi_join(samplesWithGBSandDArT %>% count(V1,V2) %>% ungroup() %>% filter(n==1))
  }),
  samplesWithGBSonly=map(samplesWithGBSonly,function(samplesWithGBSonly){
    samplesWithGBSonly %>% 
      semi_join(samplesWithGBSonly %>% count(V1,V2) %>% ungroup() %>% filter(n==1))
  }),
  dcas19_4403=map(dcas19_4403,function(dcas19_4403){
    dcas19_4403 %>% 
      semi_join(dcas19_4403 %>% count(V1,V2) %>% ungroup() %>% filter(n==1))
  }))

site_lists %>%
  mutate(samplesWithGBSonly=future_map2(Chr,samplesWithGBSonly,function(Chr,samplesWithGBSonly){
    samplesWithGBSonly %>% 
      select(V1,V2) %>% 
      arrange(V1,V2) %>% 
      write.table(.,
                  file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                              Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.sites2keep"), 
                  row.names = F, col.names = F, quote = F) 
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                              Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.vcf.gz ",
                  "--chr ",Chr," ",
                  "--positions /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_102419.sites2keep ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_read2merge_102419.vcf.gz")) }))
  
site_lists %>%
  mutate(samplesWithGBSandDArT=future_map2(Chr,samplesWithGBSandDArT,function(Chr,samplesWithGBSandDArT){
    samplesWithGBSandDArT %>% 
      select(V1,V2) %>% 
      arrange(V1,V2) %>% 
      write.table(.,
                  file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                              Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.sites2keep"), 
                  row.names = F, col.names = F, quote = F) 
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                              Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.vcf.gz ",
                  "--chr ",Chr," ",
                  "--positions /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_102419.sites2keep ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_read2merge_102419.vcf.gz")) }))

site_lists %>% 
  mutate(dcas19_4403_dcas19_4301=map2(dcas19_4403,samplesWithGBSandDArT,~.y %>% semi_join(.x)))

site_lists %>%
  mutate(dcas19_4403=future_pmap(.,function(Chr,dcas19_4403,samplesWithGBSandDArT,...){
    dcas19_4403 %>% 
      semi_join(samplesWithGBSandDArT) %>% 
      select(V1,V2) %>% 
      arrange(V1,V2) %>% 
      write.table(.,
                  file=paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                              Chr,"_DCas19_4403_102419.sites2keep"), 
                  row.names = F, col.names = F, quote = F) 
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                              Chr,"_DCas19_4403_102419.vcf.gz ",
                  "--chr ",Chr," ",
                  "--positions /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_102419.sites2keep ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_read2merge_102419.vcf.gz")) }))

Index

tibble(Chr=1:18) %>%
  mutate(Index=future_map(Chr,function(Chr){ 
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_read2merge_102419.vcf.gz"))
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_read2merge_102419.vcf.gz"))
    system(paste0("tabix -f -p vcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_DCas19_4403_read2merge_102419.vcf.gz"))
    }))
#system(paste0("tabix -f -p vcf /workdir/marnin/DCas19_4403/DCas19_4403_102419.vcf.gz"))

Merge

tibble(Chr=1:18) %>%
  mutate(Merge=future_map(Chr,function(Chr){ 
    system(paste0("bcftools merge ",
                  "--output /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_unfiltered_102419.vcf.gz ",
                  "--merge snps --output-type z --threads 6 ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSandDArT_GBSandDArTsites_unfiltered_read2merge_102419.vcf.gz ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_samplesWithGBSonly_FromGBS_allGBSsites_unfiltered_read2merge_102419.vcf.gz ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",Chr,
                  "_DCas19_4403_read2merge_102419.vcf.gz")) }))

Pre-imputation filter

Exclude dart-unique sites from missingness (and hwe?) filter to avoid their loss from the refpanel, which will only have 415/5033=8.2% potentially observed.

–minDP 5 –maxDP 50 –hwe 1e-20 (HWE p-values more extreme than this are excluded) –max-missing 0.6 (maximum 40% missing is allowed)

tibble(Chr=1:18) %>%
  mutate(PreImputeFilter=future_map(Chr,function(Chr){ 
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_unfiltered_102419.vcf.gz ",
                  "--min-alleles 2 --max-alleles 2 --minDP 5 --maxDP 50 ",
                  "--recode --stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.vcf.gz"))}))

tibble(Chr=1:18) %>%
  mutate(PreImputeFilter=future_map(Chr,function(Chr){ 
    system(paste0("vcftools --gzvcf ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.vcf.gz ",
                  "--missing-site ",
                  "--out /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419"))
    system(paste0("vcftools --gzvcf ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.vcf.gz ",
                  "--site-mean-depth ",
                  "--out /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419"))
    system(paste0("vcftools --gzvcf ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.vcf.gz ",
                  "--hardy ",
                  "--out /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419"))
  }))

stats2filterOn<-tibble(Chr=1:18) %>%
  mutate(lmiss=future_map(Chr,function(Chr){ 
    input<-read.table(paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                             Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.lmiss"),
                      stringsAsFactors = F, header = T) }),
    ldepth=future_map(Chr,function(Chr){
      input<-read.table(paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                               Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.ldepth.mean"),
                        stringsAsFactors = F, header = T) }),
    hwe=future_map(Chr,function(Chr){
      input<-read.table(paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                               Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.hwe"),
                        stringsAsFactors = F, header = T) }))

stats2filterOn %<>% 
  mutate(lmiss=map2(lmiss,ldepth,~left_join(.x %>% rename(CHROM=CHR),
                                            .y)),
         lmiss=map2(lmiss,hwe,~left_join(.x,
                                         .y %>% rename(CHROM=CHR)))) %>% 
  unnest(lmiss)
stats2filterOn %<>% 
  select(-Chr)

409959 SNPs

tibble(Chr=1:18) %>%
  mutate(PreImputeFilter=map(Chr,function(Chr){ 
    sitesThatPass<-stats2filterOn %>% 
      filter(MEAN_DEPTH<=120,
             -log10(P_HWE)<20,
             CHROM==Chr) %>% 
      select(CHROM,POS) }))
tibble(Chr=1:18) %>%
  mutate(PreImputeFilter=map(Chr,function(Chr){ 
    sitesThatPass<-stats2filterOn %>% 
      filter(MEAN_DEPTH<=120,
             -log10(P_HWE)<20,
             CHROM==Chr) %>% 
      select(CHROM,POS) 
    write.table(sitesThatPass,
                paste0("/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                       Chr,"_sitesThatPassPreImputeFilter_102419.txt"),
                row.names = F, col.names = F, quote = F) }))

tibble(Chr=1:18) %>%
  mutate(PreImputeFilter=future_map(Chr,function(Chr){ 
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_ready2filter_102419.vcf.gz ",
                  "--positions ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_sitesThatPassPreImputeFilter_102419.txt ",
                  "--recode --stdout | ",
                  "awk '$4 != \"-\" {print}' | awk '$5 != \"-\" {print}' | ",
                  "bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz"))}))

Rsync

cbsulm08 cbsulm12 cbsulm17

rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419 mw489@cbsulm08.biohpc.cornell.edu:/workdir/mw489/
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419 mw489@cbsulm12.biohpc.cornell.edu:/workdir/mw489/
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419 mw489@cbsulm17.biohpc.cornell.edu:/workdir/mw489/

# Pull data from cbsurobbins to solanine
mkdir ~/ImputationEMBRAPA_102419
scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ~/ImputationEMBRAPA_102419 

Impute EMBRAPA dataset (Beagle4.1 GL)

cbsulm17 (112) [1, 2, 6-7]

library(tidyverse); library(magrittr);
tibble(Chr=c(1,2)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))

library(tidyverse); library(magrittr);
tibble(Chr=c(6,7)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))

cbsulm12 (112) [3, 4, 11-15 done, 8-9]

library(tidyverse); library(magrittr);
tibble(Chr=c(3,4)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))
library(tidyverse); library(magrittr);
tibble(Chr=c(11,12,13,14,15)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))
library(tidyverse); library(magrittr);
tibble(Chr=c(8,9)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))

cbsulm08 (64) [5, 16-18 done, 10]

library(tidyverse); library(magrittr);
tibble(Chr=c(5)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-64
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))
tibble(Chr=c(16,17,18)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-64
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))
tibble(Chr=c(10)) %>%
  mutate(ImputeRefPanel=map(Chr,function(Chr){
    nthreads<-64
    system(paste0("java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar ",
                  "gl=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419 ",
                  "nthreads=",nthreads," niterations=10"))}))

For GB

java -Xms2g -Xmx450g -jar /programs/beagle41/beagle41.jar \
                  gl=/workdir/mw489/ImputationEMBRAPA_102419/chr1_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz \
                  out=/workdir/mw489/ImputationEMBRAPA_102419/chr1_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419 \
                  nthreads=112 niterations=10

BeagleLogs

cd /workdir/mw489/ImputationEMBRAPA_102419; 
mkdir BeagleLogs;
cp *_ImputationReferencePanel_EMBRAPA_Imputed_102419.log BeagleLogs/

Rsync

# cbsulm__ --> cbsurobbins
rsync --update --archive --verbose /workdir/mw489/ImputationEMBRAPA_102419/ mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/

# cbsurobbins --> cbsulm__
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm17.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm12.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm08.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419

Post-impute, Pre-Phase Filter

Extract and read AR2, AF, HWE

AR2>0.75, P_HWE>1e-20, MAF>0.005 [0.5%]

library(tidyverse); library(magrittr); library(furrr); options(mc.cores=18); plan(multiprocess)
pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
# pathIn<-"/workdir/mw489/ImputationEMBRAPA_102419/"

tibble(Chr=1:18) %>% 
  mutate(PreImputeFilter=future_map(Chr,function(Chr){ 
            fileIn<-paste0("vcftools --gzvcf ",pathIn,"chr",
                           Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419.vcf.gz ")
            fileOut<-paste0("--out ",pathIn,"/chr",
                            Chr,"_ImputationReferencePanel_EMBRAPA_Imputed_102419")
            system(paste0(fileIn,"--get-INFO AR2 --get-INFO AF ",fileOut))
            system(paste0(fileIn,"--hardy ",fileOut)) }))

pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
# pathIn<-"/workdir/mw489/ImputationEMBRAPA_102419/"

stats2filterOn<-tibble(Chr=1:18) %>%
    mutate(INFO=future_map(Chr,~read.table(paste0(pathIn,"chr",.,
                                                "_ImputationReferencePanel_EMBRAPA_Imputed_102419.INFO"), 
                                         stringsAsFactors = F, header = T)),
         hwe=future_map(Chr,~read.table(paste0(pathIn,"chr",.,
                                               "_ImputationReferencePanel_EMBRAPA_Imputed_102419.hwe"), 
                                        stringsAsFactors = F, header = T)))

stats2filterOn %<>% 
  select(Chr,INFO,hwe) %>% 
  mutate(INFO=map2(INFO,hwe,~left_join(.x,(.y %>% 
                                             rename(CHROM=CHR))))) %>% 
  select(-hwe) %>% 
  mutate(INFO=map(INFO,~mutate(.,MAF=ifelse(AF>0.5,1-AF,AF))))

Check what’s left

sitesPassingFilters<-stats2filterOn %>% 
  mutate(allSitesPassing=map(INFO,
                             ~filter(.,AR2>=0.75,
                                     P_HWE>1e-20,
                                     MAF>0.005) %>% 
                               select(CHROM,POS))) %>%  
  select(-INFO)
sitesPassingFilters %>% unnest(allSitesPassing) %>% nrow() # 65185 (very similar to number passing in Africa)
sitesPassingFilters

Chr allSitesPassing

1 1 <df[,2] [5,598 x 2]> 2 2 <df[,2] [4,842 x 2]> 3 3 <df[,2] [4,035 x 2]> 4 4 <df[,2] [3,391 x 2]> 5 5 <df[,2] [4,131 x 2]> 6 6 <df[,2] [3,766 x 2]> 7 7 <df[,2] [2,767 x 2]> 8 8 <df[,2] [3,043 x 2]> 9 9 <df[,2] [3,310 x 2]> 10 10 <df[,2] [4,081 x 2]> 11 11 <df[,2] [3,970 x 2]> 12 12 <df[,2] [2,875 x 2]> 13 13 <df[,2] [2,850 x 2]> 14 14 <df[,2] [3,793 x 2]> 15 15 <df[,2] [3,643 x 2]> 16 16 <df[,2] [2,518 x 2]> 17 17 <df[,2] [3,578 x 2]> 18 18 <df[,2] [2,994 x 2]>

The introgressed chromsomes 1, 4 and 14 are notoutliers in numbers of SNPs. Makes sense!

Apply filter

sitesPassingFilters %>% 
  mutate(PostImputePrePhaseFilter=future_map2(Chr,allSitesPassing,function(Chr,allSitesPassing){ 
    pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
    #pathIn<-"/workdir/mw489/ImputationEMBRAPA_102419/"
    sitesPassing_thisChr<-allSitesPassing %>% 
      select(CHROM,POS)
    write.table(sitesPassing_thisChr,
                file = paste0(pathIn,"chr",Chr,
                              "_ImputationReferencePanel_EMBRAPA_Imputed_102419.sitesPassing"),
                row.names = F, col.names = F, quote = F)
    system(paste0("vcftools --gzvcf ",pathIn,"chr",Chr,
                  "_ImputationReferencePanel_EMBRAPA_Imputed_102419.vcf.gz ",
                  "--positions ",pathIn,"chr",Chr,
                  "_ImputationReferencePanel_EMBRAPA_Imputed_102419.sitesPassing ",
                  "--recode --stdout | ",
                  "bgzip -c -@ 24 > ",
                  pathIn,"chr",Chr,
                  "_ImputationReferencePanel_EMBRAPA_Ready2Phase_102419.vcf.gz"))}))

Rsync

# cbsulm__ --> cbsurobbins
rsync --update --archive --verbose /workdir/mw489/ImputationEMBRAPA_102419 mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/

# cbsurobbins --> cbsulm__
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm17.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419

Phase EMBRAPA dataset (Beagle5 GT)

cp -r ~/CassavaGeneticMap /workdir/mw489

cbsulm17 (112)

library(tidyverse); library(magrittr);
tibble(Chr=c(1:18)) %>% 
  mutate(REFimpute_UnGenotypedSites_GBSplusDArTsamples=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx500g -jar /programs/beagle/beagle.jar ",
                  "gt=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Ready2Phase_102419.vcf.gz ",
                  "map=/workdir/mw489/CassavaGeneticMap/chr",
                  Chr,"_cassava_cM_pred.v6_91019.map ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Phased_102619 ",
                  "nthreads=",nthreads," impute=true ne=100000"))}))

BeagleLogs

cd /workdir/mw489/ImputationEMBRAPA_102419; 
#mkdir BeagleLogs;
cp *_ImputationReferencePanel_EMBRAPA_Phased_102619.log BeagleLogs/

Rsync

# cbsulm__ --> cbsurobbins
rsync --update --archive --verbose /workdir/mw489/ImputationEMBRAPA_102419/ mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/

# cbsurobbins --> cbsulm__
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm17.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm12.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm08.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419

Impute EMBRAPA C1

Extract from DCas19_4301

library(tidyverse); library(magrittr); library(furrr); options(mc.cores=18); plan(multiprocess)
pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"

system(paste0("bcftools query --list-samples ",pathIn,
              "chr1_ImputationReferencePanel_EMBRAPA_Phased_102619.vcf.gz ",
              "> ",pathIn,"chr1_ImputationReferencePanel_EMBRAPA_Phased_102619.samples"))

system(paste0("bcftools query --list-samples /workdir/marnin/EMBRAPA/",
              "chr1_DArTseqLD_C1progeny_unimputed_80718.vcf.gz ",
              "> /workdir/marnin/EMBRAPA/chr1_DArTseqLD_C1progeny_unimputed_80718.samples"))

dcas18_3633_c1_samples<-read.table(paste0("/workdir/marnin/EMBRAPA/",
                                       "chr1_DArTseqLD_C1progeny_unimputed_80718.samples"),
                                header = F, stringsAsFactors = F)$V1
dcas19_4301_samples<-read.table(paste0("/workdir/marnin/nextgenImputation2019/",
                                       "DCas19_4301_DArTseqLD_AllSites_AllChrom_raw_70919.samples"),
                                header = F, stringsAsFactors = F)$V1
refpanel_samples<-read.table(paste0(pathIn,
                                    "chr1_ImputationReferencePanel_EMBRAPA_Phased_102619.samples"),
                                header = F, stringsAsFactors = F)$V1

table(dcas18_3633_c1_samples %in% dcas19_4301_samples) # 2120 EMBRAPA C1 are in the 4301 VCF, these are what we want to impute
table(dcas19_4301_samples %in% refpanel_samples) # 182 4301 samples are already in the refpanel... 

c1_toImpute<-dcas18_3633_c1_samples %>% 
  .[. %in% dcas19_4301_samples] %>% 
  .[!. %in% refpanel_samples] # 2099 samples

write.table(c1_toImpute,
            file=paste0(pathIn,"EMBRAPA_C1progeny_FromDCas19_4301_102619.samples"),
            row.names = F, col.names = F, quote = F)

tibble(Chr=1:18) %>%
  mutate(ExtractRaw_dartSamples=future_map(Chr,function(Chr){
    pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
    #pathIn<-"/workdir/mw489/ImputationEMBRAPA_102419/"
    system(paste0("vcftools --gzvcf /workdir/marnin/nextgenImputation2019/",
                               "DCas19_4301_DArTseqLD_AllSites_AllChrom_raw_70919.vcf.gz ",
                  "--keep ",pathIn,"EMBRAPA_C1progeny_FromDCas19_4301_102619.samples ",
                  "--chr ",Chr," ",
                  "--minDP 4 --maxDP 50 ", # because using GT not PL for impute (Beagle5) 
                  "--positions ",pathIn,"chr",Chr,
                  "_ImputationReferencePanel_EMBRAPA_Imputed_102419.sitesPassing ",
                  "--recode ",
                  "--stdout | bgzip -c -@ 24 > ",
                  "/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr",
                  Chr,"_EMBRAPA_C1progeny_FromDCas19_4301_ready2impute_102419.vcf.gz")) }))

Rsync

# cbsulm__ --> cbsurobbins
rsync --update --archive --verbose /workdir/mw489/ImputationEMBRAPA_102419/ mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/

# cbsurobbins --> cbsulm__
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm17.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419/

Beagle5 REF impute

cbsulm17 (112) [1-18]

library(tidyverse); library(magrittr);
tibble(Chr=c(1:18)) %>% 
  mutate(REFimpute_EMBRAPA_C1samples=map(Chr,function(Chr){
    nthreads<-112
    system(paste0("java -Xms2g -Xmx500g -jar /programs/beagle/beagle.jar ",
                  "gt=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_EMBRAPA_C1progeny_FromDCas19_4301_ready2impute_102419.vcf.gz ",
                  "map=/workdir/mw489/CassavaGeneticMap/chr",
                  Chr,"_cassava_cM_pred.v6_91019.map ",
                  "ref=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_ImputationReferencePanel_EMBRAPA_Phased_102619.vcf.gz ",
                  "out=/workdir/mw489/ImputationEMBRAPA_102419/chr",
                  Chr,"_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619 ",
                  "nthreads=",nthreads," impute=true ne=100000"))}))

BeagleLogs

cd /workdir/mw489/ImputationEMBRAPA_102419; 
#mkdir BeagleLogs;
cp *_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.log BeagleLogs/

Rsync

# cbsulm__ --> cbsurobbins
rsync --update --archive --verbose /workdir/mw489/ImputationEMBRAPA_102419/ mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/

# cbsurobbins --> cbsulm__
rsync --update --archive --verbose /workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/ mw489@cbsulm17.biohpc.cornell.edu:/workdir/mw489/ImputationEMBRAPA_102419

Post-impute filter

AR2>0.75, P_HWE>1e-20, MAF>0.005 [0.5%]

library(tidyverse); library(magrittr); library(furrr); options(mc.cores=18); plan(multiprocess)
pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
tibble(Chr=1:18) %>% 
  mutate(PostImputeFilter=future_map(Chr,function(Chr){ 
            fileIn<-paste0("vcftools --gzvcf ",pathIn,"chr",
                           Chr,"_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.vcf.gz ")
            fileOut<-paste0("--out ",pathIn,"chr",
                            Chr,"_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619")
            system(paste0(fileIn,"--get-INFO DR2 --get-INFO AF ",fileOut))
            system(paste0(fileIn,"--hardy ",fileOut)) }))

pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
stats2filterOn<-tibble(Chr=1:18) %>%
    mutate(INFO=future_map(Chr,~read.table(paste0(pathIn,"chr",.,
                                                "_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.INFO"), 
                                         stringsAsFactors = F, header = T)),
         hwe=future_map(Chr,~read.table(paste0(pathIn,"chr",.,
                                               "_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.hwe"), 
                                        stringsAsFactors = F, header = T)))
stats2filterOn %<>% 
  select(Chr,INFO,hwe) %>% 
  mutate(INFO=map2(INFO,hwe,~left_join(.x,(.y %>% 
                                             rename(CHROM=CHR))))) %>% 
  select(-hwe)
stats2filterOn %>% 
  mutate(NotNumDR2=map_lgl(INFO,~is.numeric(.$DR2)))
stats2filterOn %<>% 
  mutate(INFO=map(INFO,
                  ~mutate(.,
                          DR2=as.numeric(DR2),
                          AF=as.numeric(AF)) %>% 
                    filter(!is.na(DR2),
                           !is.na(AF))))

stats2filterOn %<>% 
  mutate(INFO=map(INFO,~mutate(.,MAF=ifelse(AF>0.5,1-AF,AF))))

Check what’s left

sitesPassingFilters<-stats2filterOn %>% 
  mutate(allSitesPassing=map(INFO,
                             ~filter(.,DR2>=0.75,
                                     P_HWE>1e-20,
                                     MAF>0.005) %>% 
                               select(CHROM,POS))) %>%  
  select(-INFO)
stats2filterOn %>% unnest() %>% nrow() # 64886 
sitesPassingFilters %>% unnest(allSitesPassing) %>% nrow() # Only 8495 passed in the C1... :(
stats2filterOn %>% left_join(sitesPassingFilters)

Chr INFO allSitesPassing

1 1 <df[,13] [5,598 x 13]> <df[,2] [1,002 x 2]> 2 2 <df[,13] [4,842 x 13]> <df[,2] [438 x 2]>
3 3 <df[,13] [4,035 x 13]> <df[,2] [430 x 2]>
4 4 <df[,13] [3,092 x 13]> <df[,2] [239 x 2]>
5 5 <df[,13] [4,131 x 13]> <df[,2] [796 x 2]>
6 6 <df[,13] [3,766 x 13]> <df[,2] [413 x 2]>
7 7 <df[,13] [2,767 x 13]> <df[,2] [199 x 2]>
8 8 <df[,13] [3,043 x 13]> <df[,2] [532 x 2]>
9 9 <df[,13] [3,310 x 13]> <df[,2] [438 x 2]>
10 10 <df[,13] [4,081 x 13]> <df[,2] [234 x 2]>
11 11 <df[,13] [3,970 x 13]> <df[,2] [308 x 2]>
12 12 <df[,13] [2,875 x 13]> <df[,2] [407 x 2]>
13 13 <df[,13] [2,850 x 13]> <df[,2] [335 x 2]>
14 14 <df[,13] [3,793 x 13]> <df[,2] [716 x 2]>
15 15 <df[,13] [3,643 x 13]> <df[,2] [746 x 2]>
16 16 <df[,13] [2,518 x 13]> <df[,2] [267 x 2]>
17 17 <df[,13] [3,578 x 13]> <df[,2] [391 x 2]>
18 18 <df[,13] [2,994 x 13]> <df[,2] [604 x 2]>

Apply filter

sitesPassingFilters %>% 
  mutate(PostImputeFilter=future_map2(Chr,allSitesPassing,function(Chr,allSitesPassing){ 
        pathIn<-"/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/"
    sitesPassing_thisChr<-allSitesPassing %>% 
      select(CHROM,POS)
    write.table(sitesPassing_thisChr,
                file = paste0(pathIn,"chr",Chr,
                              "_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.sitesPassing"),
                row.names = F, col.names = F, quote = F)
    system(paste0("vcftools --gzvcf ",pathIn,"chr",Chr,
                  "_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.vcf.gz ",
                  "--positions ",pathIn,"chr",Chr,
                  "_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.sitesPassing ",
                  "--recode --stdout | ",
                  "bgzip -c -@ 24 > ",
                  pathIn,"chr",Chr,
                  "_EMBRAPA_C1progeny_FromDCas19_4301_REFimputedAndFiltered_102619.vcf.gz"))}))

# Pull data from cbsurobbins to solanine
scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_EMBRAPA_C1progeny_FromDCas19_4301_REFimputedAndFiltered_102619.vcf.gz ~/ImputationEMBRAPA_102419 

scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.vcf.gz ~/ImputationEMBRAPA_102419 

scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_ImputationReferencePanel_EMBRAPA_Phased_102619.vcf.gz ~/ImputationEMBRAPA_102419 

scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_ImputationReferencePanel_EMBRAPA_Ready2Phase_102419.vcf.gz ~/ImputationEMBRAPA_102419 

scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_ImputationReferencePanel_EMBRAPA_Imputed_102419.vcf.gz ~/ImputationEMBRAPA_102419 

scp mw489@cbsurobbins.biohpc.cornell.edu:/workdir/marnin/nextgenImputation2019/ImputationEMBRAPA_102419/chr\*_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz ~/ImputationEMBRAPA_102419 

Imputation is done! I have uploaded the key vcf files to ~/ImputationEMBRAPA_102419 on Solanine. Can everyone access it there?

I didn’t upload all the intermediate files. Happy to share if you want. 11 GB total.

Files in sequence of creation/imputation are:

*_ImputationReferencePanel_EMBRAPA_FilteredAndReadyToImpute_102419.vcf.gz*:
RefPanel samples (everything from L. America except EMBRAPA C1). 723 (of 869) EMBRAPA TP samples had IBD-validated matching GBS and DArT samples, which were combined for imputation. Unimputated data, but filtered.

*_ImputationReferencePanel_EMBRAPA_Imputed_102419.vcf.gz*:
RefPanel samples after imputation with Beagle4.1 GL mode.

*_ImputationReferencePanel_EMBRAPA_Ready2Phase_102419.vcf.gz*:
RefPanel samples post-impute filtered. This or the phased file would be what I would use for most analyses.

*_ImputationReferencePanel_EMBRAPA_Phased_102619.vcf.gz*: After post-impute quality filtering, Beagle5 was used to phase the RefPanel samples.

*_EMBRAPA_C1progeny_FromDCas19_4301_REFimputed_102619.vcf.gz:*
2099 EMBRAPA C1 progeny samples were extracted from the DArTseqLD report DCas19_4301 at RefPanel intersecting sites and imputed with Beagle5, using the RefPanel.

*_EMBRAPA_C1progeny_FromDCas19_4301_REFimputedAndFiltered_102619.vcf.gz*:
Post-imputation quality filters were really harsh to this dataset. Out of ~64K SNPs imputed, <9K passed the filters I’ve been using as my standard.

I’d like to request you guys all do some checks of the dataset. Does a PCA look right? Do prediction accuracies match previously? Whatever makes sense. Is there any problem with the limited number of well-imputed SNPs for the C1? I might be able to do another round of impute or something else to improve it.

Session information

sessionInfo()