Last updated: 2019-06-28

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Knit directory: apaQTL/analysis/

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Unstaged changes:
    Modified:   analysis/NuclearSpecAPAqtl.Rmd
    Modified:   analysis/NuclearSpecIncludeNotTested.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/propeQTLs_explained.Rmd
    Modified:   analysis/signalsiteanalysis.Rmd
    Modified:   code/BothFracDTPlotGeneRegions.sh
    Modified:   code/Snakefile
    Deleted:    code/Upstream10Bases_general.py
    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
    Deleted:    code/test.txt

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Rmd f00669b brimittleman 2019-06-28 add GO 
library(workflowr)
This is workflowr version 1.4.0
Run ?workflowr for help getting started
library(tidyverse)
── Attaching packages ───────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
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── Conflicts ──────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
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I want to do a quick gene set enrichemnt for the apaQTLs using http://cbl-gorilla.cs.technion.ac.il. I need to get the genes we test for apaQTLs in each fraction as a background set and those we find as significant as the test set.

totQTL=read.table("../data/apaQTLs/Total_apaQTLs4pc_5fdr.txt", header = T, stringsAsFactors = F) %>% select(Gene) %>% unique()
write.table(totQTL, file="../data/apaQTLs/TotalapaQTLGenes.txt", col.names = F, row.names = F, quote = F)
nucQTL=read.table("../data/apaQTLs/Nuclear_apaQTLs4pc_5fdr.txt", stringsAsFactors = F, header = T) %>% select(Gene) %>% unique()
write.table(nucQTL, file="../data/apaQTLs/NuclearapaQTLGenes.txt", col.names = F, row.names = F, quote = F)

Genes we tested:

tottested=read.table("../data/apaQTLPermuted_4pc/APApeak_Phenotype_GeneLocAnno.Total_permResBH.txt", header = T, stringsAsFactors = F) %>% separate(pid, into=c("chr", "start", "end", "peakID"),sep=":") %>% separate(peakID, into=c("gene", "loc", "strand", "PAS"), sep="_") %>% select(gene) %>% unique()
write.table(tottested, file="../data/apaQTLs/TestedTotalapaQTLGenes.txt", col.names = F, row.names = F, quote = F)

nuctested=read.table("../data/apaQTLPermuted_4pc/APApeak_Phenotype_GeneLocAnno.Nuclear_permResBH.txt", header = T, stringsAsFactors = F) %>% separate(pid, into=c("chr", "start", "end", "peakID"),sep=":") %>% separate(peakID, into=c("gene", "loc", "strand", "PAS"), sep="_") %>% select(gene) %>% unique()

write.table(nuctested, file="../data/apaQTLs/TestedNuclearapaQTLGenes.txt", col.names = F, row.names = F, quote = F)

Total res:

Processes - cellular detoxification of aldehyde, developmental growth,growth, nucleotide transmembrane transport,cellular amide metabolic process function- aminopeptidase activity, nucleotide transmembrane transporter activity, metalloaminopeptidase activity, SNAP receptor activity component- SPOTS complex, endoplasmic reticulum palmitoyltransferase complex, protein-cysteine S-palmitoyltransferase complex, serine C-palmitoyltransferase complex

Nuclear res:

no results


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 workflowr_1.4.0

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    backports_1.1.2  scales_1.0.0     htmltools_0.3.6 
[41] rvest_0.3.2      assertthat_0.2.0 colorspace_1.3-2 stringi_1.2.4   
[45] lazyeval_0.2.1   munsell_0.5.0    broom_0.5.1      crayon_1.3.4