Total and Nuclear QTL sharing

Last updated: 2019-06-11

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Knit directory: apaQTL/analysis/

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Unstaged changes:
    Modified:   analysis/DiffIsoAnalysis.Rmd
    Modified:   analysis/PASusageQC.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/choosePCs.Rmd
    Modified:   analysis/corrbetweenind.Rmd
    Modified:   analysis/exvunexpeQTL.Rmd
    Modified:   analysis/mapapaQTL.Rmd
    Modified:   analysis/motifDisruption.Rmd
    Modified:   analysis/nascenttranscription.Rmd
    Modified:   analysis/nucintronicanalysis.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/rna_netseq_h3k12ac.Rmd
    Modified:   code/BothFracDTPlotGeneRegions.sh
    Modified:   code/Snakefile
    Deleted:    code/Upstream10Bases_general.py
    Modified:   code/apaQTLCorrectPvalMakeQQ.R
    Modified:   code/apaQTL_permuted.sh
    Modified:   code/apaQTLsnake.err
    Modified:   code/bam2bw.sh
    Modified:   code/bed2saf.py
    Modified:   code/cluster.json
    Modified:   code/config.yaml
    Deleted:    code/test.txt

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 R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File	Version	Author	Date	Message
html	d117338	brimittleman	2019-05-20	Build site.
Rmd	7da06f5	brimittleman	2019-05-20	switch log effect
html	a88eedf	brimittleman	2019-05-20	Build site.
Rmd	8f883d8	brimittleman	2019-05-20	add overlap analysis

This analysis will investigate the sharing between total and nuclear apaQTls first by calculating the pi1 statistic and second by looking at the correlation of effect sizes.

library(tidyverse)

── Attaching packages ───────────────────────────────────────────────────────────── tidyverse 1.2.1 ──

✔ ggplot2 3.1.1       ✔ purrr   0.3.2  
✔ tibble  2.1.1       ✔ dplyr   0.8.0.1
✔ tidyr   0.8.3       ✔ stringr 1.3.1  
✔ readr   1.3.1       ✔ forcats 0.3.0

── Conflicts ──────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library(reshape2)


Attaching package: 'reshape2'

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

    smiths

library(workflowr)

This is workflowr version 1.3.0
Run ?workflowr for help getting started

library(qvalue)

Pi 1 sharing

Concatinate nominal results and run

mkdir ../data/QTLoverlap/
python qtlsPvalOppFrac.py ../data/apaQTLs/Total_apaQTLs4pc_5fdr.txt ../data/apaQTLNominal_4pc/APApeak_Phenotype_GeneLocAnno.Nuclear.5perc.fc.gz.qqnorm_AllChrom.txt ../data/QTLoverlap/TotalQTLinNuclearNominal.txt  


python qtlsPvalOppFrac.py ../data/apaQTLs/Nuclear_apaQTLs4pc_5fdr.txt ../data/apaQTLNominal_4pc/APApeak_Phenotype_GeneLocAnno.Total.5perc.fc.gz.qqnorm_AllChrom.txt ../data/QTLoverlap/NuclearQTLinTotalNominal.txt

totAPAinNuc=read.table("../data/QTLoverlap/TotalQTLinNuclearNominal.txt", header = F, stringsAsFactors = F, col.names=c("peakID", "snp", "dist", "pval", "slope"))
qval_tot=pi0est(totAPAinNuc$pval, pi0.method = "bootstrap")

nucAPAinTot=read.table("../data/QTLoverlap/NuclearQTLinTotalNominal.txt", header = F, stringsAsFactors = F, col.names=c("peakID", "snp", "dist", "pval", "slope"))
qval_nuc=pi0est(nucAPAinTot$pval, pi0.method = "bootstrap")

par(mfrow=c(1,2))
hist(totAPAinNuc$pval, xlab="Nuclear Pvalue", main="Significant Total APA QTLs \n Nuclear")
text(.8,300, paste("pi_1=", round((1-qval_tot$pi0), digit=3), sep=" "))
hist(nucAPAinTot$pval, xlab="Total Pvalue", main="Significant Nuclear APA QTLs \n Total")
text(.8,450, paste("pi_1=", round((1-qval_nuc$pi0), digit=3), sep=" "))

Version	Author	Date
a88eedf	brimittleman	2019-05-20

Effect size sharing:

I need to get the nominal effect sizes. I can use the script I wrote above but put the same fraction in for the qtl and nom values.


python qtlsPvalOppFrac.py ../data/apaQTLs/Total_apaQTLs4pc_5fdr.txt ../data/apaQTLNominal_4pc/APApeak_Phenotype_GeneLocAnno.Total.5perc.fc.gz.qqnorm_AllChrom.txt ../data/QTLoverlap/TotalQTLinTotalNominal.txt  


python qtlsPvalOppFrac.py ../data/apaQTLs/Nuclear_apaQTLs4pc_5fdr.txt ../data/apaQTLNominal_4pc/APApeak_Phenotype_GeneLocAnno.Nuclear.5perc.fc.gz.qqnorm_AllChrom.txt ../data/QTLoverlap/NuclearQTLinNuclearNominal.txt

totAPAinTot=read.table("../data/QTLoverlap/TotalQTLinTotalNominal.txt", header = F, stringsAsFactors = F, col.names=c("peakID", "snp", "dist", "pval", "slope")) %>% dplyr::select(peakID, snp, slope) %>% dplyr::rename("Originalslope"=slope)


nucAPAinNuc=read.table("../data/QTLoverlap/NuclearQTLinNuclearNominal.txt", header = F, stringsAsFactors = F, col.names=c("peakID", "snp", "dist", "pval", "slope")) %>% dplyr::select(peakID, snp, slope)%>% dplyr::rename("Originalslope"=slope)

Join the data frames:

Total:

TotBoth= totAPAinNuc %>% inner_join(totAPAinTot,by=c("peakID", "snp"))
summary(lm(log10(TotBoth$slope) ~ log10(TotBoth$Originalslope)))

Warning in eval(predvars, data, env): NaNs produced

Warning in eval(predvars, data, env): NaNs produced


Call:
lm(formula = log10(TotBoth$slope) ~ log10(TotBoth$Originalslope))

Residuals:
     Min       1Q   Median       3Q      Max 
-2.53182 -0.05434  0.09995  0.17233  0.33003 

Coefficients:
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                  -0.14280    0.02246  -6.357 1.04e-09 ***
log10(TotBoth$Originalslope)  0.93453    0.14751   6.336 1.17e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.3288 on 238 degrees of freedom
  (230 observations deleted due to missingness)
Multiple R-squared:  0.1443,    Adjusted R-squared:  0.1407 
F-statistic: 40.14 on 1 and 238 DF,  p-value: 1.172e-09

ggplot(TotBoth, aes(x=log10(Originalslope), y=log10(slope)))+geom_point() + geom_smooth(method="lm") + labs(title="Total apaQTL effect sizes", x="Effect size in Nuclear",y="Effect size in Total") + geom_density_2d(col="red")

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

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Warning: Removed 230 rows containing non-finite values (stat_smooth).

Warning: Removed 230 rows containing non-finite values (stat_density2d).

Warning: Removed 230 rows containing missing values (geom_point).

Version	Author	Date
d117338	brimittleman	2019-05-20
a88eedf	brimittleman	2019-05-20

NucBoth= nucAPAinTot %>% inner_join(nucAPAinNuc,by=c("peakID", "snp"))
summary(lm(log10(NucBoth$slope) ~ log10(NucBoth$Originalslope)))

Warning in eval(predvars, data, env): NaNs produced

Warning in eval(predvars, data, env): NaNs produced


Call:
lm(formula = log10(NucBoth$slope) ~ log10(NucBoth$Originalslope))

Residuals:
     Min       1Q   Median       3Q      Max 
-2.76127 -0.07345  0.09761  0.20925  0.43489 

Coefficients:
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                  -0.26243    0.01766 -14.861   <2e-16 ***
log10(NucBoth$Originalslope)  1.16826    0.11813   9.889   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.3681 on 461 degrees of freedom
  (396 observations deleted due to missingness)
Multiple R-squared:  0.175, Adjusted R-squared:  0.1732 
F-statistic:  97.8 on 1 and 461 DF,  p-value: < 2.2e-16

ggplot(NucBoth, aes(x=log10(Originalslope), y=log10(slope)))+geom_point() + geom_smooth(method="lm") + labs(title="Nuclear apaQTL effect sizes", x="Effect size in Total",y="Effect size in Nuclear") + geom_density_2d(col="red")

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning in FUN(X[[i]], ...): NaNs produced

Warning: Removed 396 rows containing non-finite values (stat_smooth).

Warning: Removed 396 rows containing non-finite values (stat_density2d).

Warning: Removed 396 rows containing missing values (geom_point).

Version	Author	Date
d117338	brimittleman	2019-05-20
a88eedf	brimittleman	2019-05-20

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] qvalue_2.14.0   workflowr_1.3.0 reshape2_1.4.3  forcats_0.3.0  
 [5] stringr_1.3.1   dplyr_0.8.0.1   purrr_0.3.2     readr_1.3.1    
 [9] tidyr_0.8.3     tibble_2.1.1    ggplot2_3.1.1   tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0       cellranger_1.1.0 pillar_1.3.1     compiler_3.5.1  
 [5] git2r_0.25.2     plyr_1.8.4       tools_3.5.1      digest_0.6.18   
 [9] lubridate_1.7.4  jsonlite_1.6     evaluate_0.12    nlme_3.1-137    
[13] gtable_0.2.0     lattice_0.20-38  pkgconfig_2.0.2  rlang_0.3.1     
[17] cli_1.0.1        rstudioapi_0.10  yaml_2.2.0       haven_1.1.2     
[21] withr_2.1.2      xml2_1.2.0       httr_1.3.1       knitr_1.20      
[25] hms_0.4.2        generics_0.0.2   fs_1.2.6         rprojroot_1.3-2 
[29] grid_3.5.1       tidyselect_0.2.5 glue_1.3.0       R6_2.3.0        
[33] readxl_1.1.0     rmarkdown_1.10   modelr_0.1.2     magrittr_1.5    
[37] whisker_0.3-2    MASS_7.3-51.1    splines_3.5.1    backports_1.1.2 
[41] scales_1.0.0     htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0
[45] colorspace_1.3-2 labeling_0.3     stringi_1.2.4    lazyeval_0.2.1  
[49] munsell_0.5.0    broom_0.5.1      crayon_1.3.4

Total and Nuclear QTL sharing

Briana Mittleman

5/20/2019