Last updated: 2019-09-11

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Knit directory: apaQTL/analysis/

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Unstaged changes:
    Modified:   analysis/NuclearSpecIncludeNotTested.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/compareAnnotatedpas.Rmd
    Modified:   analysis/nucSpecinEQTLs.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/propeQTLs_explained.Rmd
    Modified:   analysis/version15bpfilter.Rmd
    Modified:   code/BothFracDTPlotGeneRegions.sh
    Modified:   code/Snakefile
    Modified:   code/SnakefilefiltPAS
    Modified:   code/apaQTLCorrectPvalMakeQQ.R
    Modified:   code/apaQTL_Nominal.sh
    Modified:   code/apaQTL_permuted.sh
    Modified:   code/apaQTLsnake.err
    Modified:   code/bam2bw.sh
    Modified:   code/bed2saf.py
    Modified:   code/cluster.json
    Modified:   code/clusterfiltPAS.json
    Modified:   code/config.yaml
    Modified:   code/environment.yaml
    Modified:   code/makePheno.py
    Modified:   code/mergeAllBam.sh
    Modified:   code/mergeByFracBam.sh
    Modified:   code/mergePeaks.sh
    Modified:   code/peakFC.sh
    Modified:   code/snakemake.batch
    Modified:   code/snakemakePAS.batch
    Modified:   code/snakemakefiltPAS.batch
    Modified:   code/submit-snakemake.sh
    Modified:   code/submit-snakemakePAS.sh
    Modified:   code/submit-snakemakefiltPAS.sh
    Deleted:    code/test.txt
    Modified:   data/MetaDataSequencing.txt
    Deleted:    reads_graphs.Rmd

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
Rmd f341c6f brimittleman 2019-09-11 add creation of supp table
html 92d333a brimittleman 2019-09-02 Build site.
Rmd ff85650 brimittleman 2019-09-02 add p not e or r
html 737e8d1 brimittleman 2019-08-31 Build site.
Rmd fddc36b brimittleman 2019-08-31 add ribo and LZ info
html 16cbaa3 brimittleman 2019-08-30 Build site.
Rmd 80f8466 brimittleman 2019-08-30 add riboQTL and fix expression name switch
html f0e99cb brimittleman 2019-08-30 Build site.
Rmd d1bef28 brimittleman 2019-08-30 add number of examples
html 1e58d07 brimittleman 2019-06-27 Build site.
Rmd db5d2e6 brimittleman 2019-06-27 add pqtl example 
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()

Protien specific qtl example

totQTL=read.table("../data/apaQTLs/Total_apaQTLs4pc_5fdr.txt", header = T, stringsAsFactors = F) 
nucQTL=read.table("../data/apaQTLs/Nuclear_apaQTLs4pc_5fdr.txt", stringsAsFactors = F, header = T)

rs9820529

peak93951

genohead=as.data.frame(read.table("../data/ExampleQTLPlots/genotypeHeader.txt", stringsAsFactors = F, header = F)[,10:128] %>% t())
colnames(genohead)=c("header")
genotype=as.data.frame(read.table("../data/ExampleQTLPlots/EIF2A_TotalPeaksGenotype.txt", stringsAsFactors = F, header = F) [,10:128] %>% t())

full_geno=bind_cols(Ind=genohead$header, dose=genotype$V1) %>% mutate(numdose=round(dose), genotype=ifelse(numdose==0, "TT", ifelse(numdose==1, "TA", "AA")))

RNAhead=as.data.frame(read.table("../data/molPhenos/RNAhead.txt", stringsAsFactors = F, header = F)[,5:73] %>% t())

RNApheno=as.data.frame(read.table("../data/molPhenos/RNA_EIF2a.txt", stringsAsFactors = F, header = F) [,5:73] %>% t())

full_pheno=bind_cols(Ind=RNAhead$V1, Expression=RNApheno$V1)

allRNA=full_geno %>% inner_join(full_pheno, by="Ind")
Warning: Column `Ind` joining factors with different levels, coercing to
character vector
allRNA$genotype=as.factor(allRNA$genotype)

ggplot(allRNA, aes(x=genotype, y=Expression,group=genotype, fill=genotype)) + geom_boxplot() + geom_jitter()+scale_fill_brewer(palette = "Dark2") + labs(title="eQTL: EIF2A - rs9820529") + theme(legend.position = "bottom")

Version Author Date
f0e99cb brimittleman 2019-08-30
1e58d07 brimittleman 2019-06-27 
prothead=as.data.frame(read.table("../data/molPhenos/ProtHead.txt", stringsAsFactors = F, header = F)[,5:66] %>% t())

protpheno=as.data.frame(read.table("../data/molPhenos/prot_EIF2A.txt", stringsAsFactors = F, header = F) [,5:66] %>% t())

full_phenoprot=bind_cols(Ind=prothead$V1, Expression=protpheno$V1)

allprot=full_geno %>% inner_join(full_phenoprot, by="Ind")
Warning: Column `Ind` joining factors with different levels, coercing to
character vector
allprot$genotype=as.factor(allprot$genotype)

ggplot(allprot, aes(x=genotype, y=Expression,group=genotype, fill=genotype)) + geom_boxplot() + geom_jitter()+scale_fill_brewer(palette = "Dark2") + labs(title="pQTL: EIF2A - rs9820529", y="Protein Level")+ theme(legend.position = "bottom")

Version Author Date
f0e99cb brimittleman 2019-08-30
1e58d07 brimittleman 2019-06-27

Ribo plot:

ENSG00000144895

ribohead=as.data.frame(read.table("../data/molPhenos/RiboHead.txt", stringsAsFactors = F, header = F)[,5:74] %>% t())

ribopheno=as.data.frame(read.table("../data/molPhenos/ribo_EIF2A.txt", stringsAsFactors = F, header = F) [,5:74] %>% t())

full_phenoribo=bind_cols(Ind=ribohead$V1, Expression=ribopheno$V1)

allribo=full_geno %>% inner_join(full_phenoribo, by="Ind")
Warning: Column `Ind` joining factors with different levels, coercing to
character vector
allribo$genotype=as.factor(allribo$genotype)

ggplot(allribo, aes(x=genotype, y=Expression,group=genotype, fill=genotype)) + geom_boxplot() + geom_jitter()+scale_fill_brewer(palette = "Dark2") + labs(title="riboQTL: EIF2A - rs9820529", y="Ribo Level")+ theme(legend.position = "bottom")

Version Author Date
737e8d1 brimittleman 2019-08-31

Make Locus zoom files:

prot_LZ=read.table("../data/locusZoom/Prot.EIF2A.nom.txt", stringsAsFactors = F, col.names = c("PeakID", "SNP", "Dist", "P","slope"))  %>% select( SNP, P)

write.table(prot_LZ,"../data/locusZoom/ProtEIF2ALZ.txt", col.names = T, row.names = F, quote = F)



ribo_LZ=read.table("../data/locusZoom/Ribo.EIF2A.nom.txt", stringsAsFactors = F, col.names = c("PeakID", "SNP", "Dist", "P","slope"))  %>% select( SNP, P)

write.table(ribo_LZ,"../data/locusZoom/RiboEIF2ALZ.txt", col.names = T, row.names = F, quote = F)



ribo_LZ=read.table("../data/locusZoom/RNA.EIF2A.nom.txt", stringsAsFactors = F, col.names = c("PeakID", "SNP", "Dist", "P","slope"))  %>% select( SNP, P)

write.table(ribo_LZ,"../data/locusZoom/RNAEIF2ALZ.txt", col.names = T, row.names = F, quote = F)

Broader: Ask how many examples:

Ask for apaQTLs sig in P not in E

mkdir ../data/pQTLoverlap
python apaInPandE.py

apaQTL=read.table("../data/apaQTLs/Nuclear_apaQTLs4pc_5fdr.txt", stringsAsFactors = F, header = T)
apainE=read.table("../data/pQTLoverlap/NucAPAinExpression.txt", stringsAsFactors = F, col.names = c("Gene", 'sid','dist', 'Exppval', 'Eslope')) %>% select(Gene, sid, Exppval,Eslope)
apainP=read.table("../data/pQTLoverlap/NucAPAinProt.txt", stringsAsFactors = F, col.names = c("Gene", 'sid','dist', 'Protppval', 'Pslope')) %>% select(Gene, sid, Protppval ,Pslope)

#combine  
allQTL=apaQTL %>% inner_join(apainE,by=c("Gene", "sid")) %>% inner_join(apainP, by=c("Gene","sid"))


#select sig in p not e
pnote=allQTL %>% filter(Exppval>.05) %>% filter(Protppval<.05) %>% select(Gene, sid) %>% unique()

add Ribo data.

python apainRibo.py
apainRibo=read.table("../data/pQTLoverlap/NucAPAinRibo.txt", stringsAsFactors = F, col.names = c("Gene", 'sid','dist', 'Riboppval', 'Riboslope')) %>% select(Gene, sid, Riboppval,Riboslope)

#combine  
allQTL_withribo=apaQTL %>% inner_join(apainE,by=c("Gene", "sid")) %>% inner_join(apainP, by=c("Gene","sid")) %>% inner_join(apainRibo, by=c("Gene","sid"))

#select sig in p not e
pnoteorr=allQTL_withribo %>% filter(Exppval>.05) %>% filter(Protppval<.05) %>% filter(Riboppval<.05) %>%  select(Gene, sid) %>% unique()

nrow(pnoteorr)
[1] 5

Make supplementary table:

pnote_withR=allQTL_withribo  %>% filter(Exppval>.05) %>% filter(Protppval<.05) %>% select(Gene, Loc, Peak, sid,bpval, slope, Exppval,Eslope, Protppval, Pslope, Riboppval, Riboslope)
colnames(pnote_withR)=c("Gene", "PAS_Loc", "PAS_ID", "SNP", "apa_pvalue","apa_EffectSize", "expression_pvalue","expresion_EffectSize", "protein_pvalue", "protein_EffectSize", "ribo_pvalue", "ribo_EffectSize")
write.table(pnote_withR, file="../data/ExpressionIndependentapaQTLs.txt", col.names = T, row.names =F, quote = F)

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] forcats_0.3.0   stringr_1.3.1   dplyr_0.8.0.1   purrr_0.3.2    
[5] readr_1.3.1     tidyr_0.8.3     tibble_2.1.1    ggplot2_3.1.1  
[9] tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0         RColorBrewer_1.1-2 cellranger_1.1.0  
 [4] plyr_1.8.4         compiler_3.5.1     pillar_1.3.1      
 [7] git2r_0.25.2       highr_0.7          workflowr_1.4.0   
[10] tools_3.5.1        digest_0.6.18      lubridate_1.7.4   
[13] jsonlite_1.6       evaluate_0.12      nlme_3.1-137      
[16] gtable_0.2.0       lattice_0.20-38    pkgconfig_2.0.2   
[19] rlang_0.4.0        cli_1.1.0          rstudioapi_0.10   
[22] yaml_2.2.0         haven_1.1.2        withr_2.1.2       
[25] xml2_1.2.0         httr_1.3.1         knitr_1.20        
[28] hms_0.4.2          generics_0.0.2     fs_1.3.1          
[31] rprojroot_1.3-2    grid_3.5.1         tidyselect_0.2.5  
[34] glue_1.3.0         R6_2.3.0           readxl_1.1.0      
[37] rmarkdown_1.10     modelr_0.1.2       magrittr_1.5      
[40] whisker_0.3-2      backports_1.1.2    scales_1.0.0      
[43] htmltools_0.3.6    rvest_0.3.2        assertthat_0.2.0  
[46] colorspace_1.3-2   labeling_0.3       stringi_1.2.4     
[49] lazyeval_0.2.1     munsell_0.5.0      broom_0.5.1       
[52] crayon_1.3.4