Call aditional molecular QTLs

Last updated: 2018-09-26

workflowr checks: (Click a bullet for more information)

✔ 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(12345)

The command set.seed(12345) 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.

✔ Repository version: fa7f707

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

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:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    output/.DS_Store

Untracked files:
    Untracked:  analysis/PeakToGeneAssignment.Rmd
    Untracked:  analysis/ncbiRefSeq_sm.sort.mRNA.bed
    Untracked:  analysis/snake.config.notes.Rmd
    Untracked:  analysis/verifyBAM.Rmd
    Untracked:  data/18486.genecov.txt
    Untracked:  data/APApeaksYL.total.inbrain.bed
    Untracked:  data/NuclearApaQTLs.txt
    Untracked:  data/RNAkalisto/
    Untracked:  data/TotalApaQTLs.txt
    Untracked:  data/Totalpeaks_filtered_clean.bed
    Untracked:  data/YL-SP-18486-T-combined-genecov.txt
    Untracked:  data/YL-SP-18486-T_S9_R1_001-genecov.txt
    Untracked:  data/bedgraph_peaks/
    Untracked:  data/bin200.5.T.nuccov.bed
    Untracked:  data/bin200.Anuccov.bed
    Untracked:  data/bin200.nuccov.bed
    Untracked:  data/clean_peaks/
    Untracked:  data/comb_map_stats.csv
    Untracked:  data/comb_map_stats.xlsx
    Untracked:  data/comb_map_stats_39ind.csv
    Untracked:  data/combined_reads_mapped_three_prime_seq.csv
    Untracked:  data/gencov.test.csv
    Untracked:  data/gencov.test.txt
    Untracked:  data/gencov_zero.test.csv
    Untracked:  data/gencov_zero.test.txt
    Untracked:  data/gene_cov/
    Untracked:  data/joined
    Untracked:  data/leafcutter/
    Untracked:  data/merged_combined_YL-SP-threeprimeseq.bg
    Untracked:  data/nom_QTL/
    Untracked:  data/nom_QTL_opp/
    Untracked:  data/nuc6up/
    Untracked:  data/other_qtls/
    Untracked:  data/peakPerRefSeqGene/
    Untracked:  data/perm_QTL/
    Untracked:  data/perm_QTL_opp/
    Untracked:  data/reads_mapped_three_prime_seq.csv
    Untracked:  data/smash.cov.results.bed
    Untracked:  data/smash.cov.results.csv
    Untracked:  data/smash.cov.results.txt
    Untracked:  data/smash_testregion/
    Untracked:  data/ssFC200.cov.bed
    Untracked:  data/temp.file1
    Untracked:  data/temp.file2
    Untracked:  data/temp.gencov.test.txt
    Untracked:  data/temp.gencov_zero.test.txt
    Untracked:  output/picard/
    Untracked:  output/plots/
    Untracked:  output/qual.fig2.pdf

Unstaged changes:
    Modified:   analysis/28ind.peak.explore.Rmd
    Modified:   analysis/cleanupdtseq.internalpriming.Rmd
    Modified:   analysis/dif.iso.usage.leafcutter.Rmd
    Modified:   analysis/diff_iso_pipeline.Rmd
    Modified:   analysis/explore.filters.Rmd
    Modified:   analysis/overlap_qtls.Rmd
    Modified:   analysis/peakOverlap_oppstrand.Rmd
    Modified:   analysis/pheno.leaf.comb.Rmd
    Modified:   analysis/test.max2.Rmd
    Modified:   code/Snakefile

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.

Expand here to see past versions:

File	Version	Author	Date	Message
Rmd	fa7f707	Briana Mittleman	2018-09-26	ribo QTL code

I will use this analysis file to recall the other molecular QTLs using the same VCF files I am using for the APAqtls. This is important because we want to overlap QTLs called with the same genotype information.

processed (WASP+normalized) 4sU-seq (30m)
processed (WASP+normalized) 4sU-seq (60m)
processed (WASP+normalized) RNA-seq (Pickrell)
processed (WASP+normalized) RNA-seq (GEUVADIS)
processed (WASP+normalized) ribo-seq
LiftOver from (Battle et al., 2015) protein

I am download the processed data from http://eqtl.uchicago.edu/jointLCL/ and putting it in /project2/gilad/briana/threeprimeseq/data/molecular_phenos.

The protein file is already in the format needed for fastQTL. I need to change the headers to include the NA before the individuals.I will need to use:

bgzip phenotypes.bed && tabix -p bed phenotypes.bed.gz

To index the file for the program.

I will create a python script that adds the NA to the individuals.

def main(inF, outF):
  infile= open(inF, "r")
  fout = open(outF,'w')
  for i, line in enumerate(infile):
      if i == 0:
          linelist=line.split()
          for i, item in enumerate(linelist):
              if i > 3:
                  linelist[i]="NA" + item
          fout.write("  ".join(linelist) + '\n' )
      else:
         fout.write(line)
  fout.close()


if __name__ == "__main__":
    import sys
    inF = sys.argv[1]
    outF= sys.argv[2]
    main(inF, outF)

Next step is to get the PCs to use as covariates in the analysis.

https://qtltools.github.io/qtltools/

This package is in /project/gilad/software/midway1/ and was installed by Peter Carbaneto from the RCC. I can add this to my path with:

export PATH=/project/gilad/software/midway1/qtltools-1.0:$PATH

I am going to use the QTLtools pca function. I need to run this on midway1.


QTLtools pca --bed /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.bed.gz --scale --center --out /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.bed.PC.txt

#keep top 5 PCs for analysis
head -n 6 fastqtl_qqnorm_ribo_phase2.fixed.bed.PC.txt.pca > fastqtl_qqnorm_ribo_phase2.fixed.bed.5PCs.txt.pca

I then make a samples file wit the head of the PCA file. Remove 19192,19193 from sample file I need to make 1 vcf file with all of the chroms to run this.

riboQTL.nom.sh

#!/bin/bash


#SBATCH --job-name=riboQTL.nom
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=riboQTL.nom.out
#SBATCH --error=riboQTL.nom.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END

for i in $(seq 1 30)
do
/home/brimittleman/software/bin/FastQTL/bin/fastQTL.static --vcf /project2/gilad/briana/YRI_geno_hg19/allChrom.dose.filt.vcf.gz  --cov /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.bed.5PCs_tab.txt.pca --bed /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.noChr.bed.gz --out /project2/gilad/briana/threeprimeseq/data/molecular_QTLs/nom/fastqtl_qqnorm_ribo_phase2.fixed.nominal.out --chunk $i 30  --window 5e4 --include-samples /project2/gilad/briana/threeprimeseq/data/molecular_phenos/samples.txt
done

problem chr in pheno file and not in vcf


 sed 's/^chr//'  fastqtl_qqnorm_ribo_phase2.fixed.bed > fastqtl_qqnorm_ribo_phase2.fixed.noChr.bed

try changing /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.bed.5PCs.txt.pca first part of header to id like in the FastQTL site. and use tr to make it tap deliminated from " "

riboQTL.perm.sh

#!/bin/bash


#SBATCH --job-name=riboQTL.perm
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=riboQTL.perm.out
#SBATCH --error=riboQTL.perm.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END

for i in $(seq 1 30)
do
/home/brimittleman/software/bin/FastQTL/bin/fastQTL.static --permute 1000  --vcf /project2/gilad/briana/YRI_geno_hg19/allChrom.dose.filt.vcf.gz  --cov /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.bed.5PCs_tab.txt.pca --bed /project2/gilad/briana/threeprimeseq/data/molecular_phenos/fastqtl_qqnorm_ribo_phase2.fixed.noChr.bed.gz --out /project2/gilad/briana/threeprimeseq/data/molecular_QTLs/perm/fastqtl_qqnorm_ribo_phase2.fixed.perm.chunk$i.out --chunk $i 30  --window 5e4 --include-samples /project2/gilad/briana/threeprimeseq/data/molecular_phenos/samples.txt
done

Session information

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/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     

loaded via a namespace (and not attached):
 [1] workflowr_1.1.1   Rcpp_0.12.18      digest_0.6.16    
 [4] rprojroot_1.3-2   R.methodsS3_1.7.1 backports_1.1.2  
 [7] git2r_0.23.0      magrittr_1.5      evaluate_0.11    
[10] stringi_1.2.4     whisker_0.3-2     R.oo_1.22.0      
[13] R.utils_2.7.0     rmarkdown_1.10    tools_3.5.1      
[16] stringr_1.3.1     yaml_2.2.0        compiler_3.5.1   
[19] htmltools_0.3.6   knitr_1.20

This reproducible R Markdown analysis was created with workflowr 1.1.1

Call aditional molecular QTLs

Briana Mittleman

9/25/2018

Session information