From peak to PAS

Last updated: 2020-04-10

Checks: 7 0

Knit directory: Comparative_APA/analysis/

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Unstaged changes:
    Modified:   analysis/ExploredAPA.Rmd
    Modified:   analysis/MMExpreiment.Rmd
    Modified:   analysis/OppositeMap.Rmd
    Modified:   analysis/TotalVNuclearBothSpecies.Rmd
    Modified:   analysis/annotationInfo.Rmd
    Modified:   analysis/changeMisprimcut.Rmd
    Modified:   analysis/comp2apaQTLPAS.Rmd
    Modified:   analysis/correlationPhenos.Rmd
    Modified:   analysis/establishCutoffs.Rmd
    Modified:   analysis/investigatePantro5.Rmd
    Modified:   analysis/multiMap.Rmd
    Modified:   analysis/pol2.Rmd
    Modified:   analysis/speciesSpecific.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
html	ceb56ae	brimittleman	2020-01-09	Build site.
Rmd	4a1eaf2	brimittleman	2020-01-09	fix metadata out
html	dd02dab	brimittleman	2020-01-09	Build site.
Rmd	13448ce	brimittleman	2020-01-09	add sort code
html	a41141b	brimittleman	2020-01-09	Build site.
Rmd	93ced1e	brimittleman	2020-01-09	peak 2 pas

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(workflowr)

This is workflowr version 1.6.0
Run ?workflowr for help getting started

In this analysis I want to make correct strand and coordinate bed files for the PAS .

The final PAS are in /project2/gilad/briana/Comparative_APA/data/Peaks_5perc/Peaks_5perc_either_HumanCoordHummanUsage.bed

I will fix the strand and put them in a PAS folder

mkdir ../data/PAS

Human

#fix strand
PAS=read.table("../data/Peaks_5perc/Peaks_5perc_either_HumanCoordHummanUsage.bed", header=T,stringsAsFactors = F) %>% mutate(strandFix=ifelse(strand =="+","-","+")) %>% dplyr::select(-strand)

write.table(PAS,"../data/PAS/PAS_5perc_either_HumanCoordHummanUsage.bed",col.names = F, row.names = F, quote = F, sep="\t")

sort -k1,1 -k2,2n ../data/PAS/PAS_5perc_either_HumanCoordHummanUsage.bed > ../data/PAS/PAS_5perc_either_HumanCoordHummanUsage.sort.bed

chimp:

strandinfo=PAS %>% dplyr::select(PAS, strandFix)
PASChimpUsage=read.table("../data/Peaks_5perc/Peaks_5perc_either_bothUsage.txt",header=T,stringsAsFactors = F) %>% inner_join(strandinfo, by="PAS") %>% dplyr::select(chr,start,end, PAS,Chimp, strandFix)

write.table(PASChimpUsage,"../data/PAS/PAS_5perc_either_HumanCoordChimpUsage.bed",col.names = F, row.names = F, quote = F, sep="\t")

Lift to get the chimp coordinates:

sbatch Lift5perPAS.sh

sort -k1,1 -k2,2n  ../data/PAS/PAS_5perc_either_ChimpCoordChimpUsage.bed > ../data/PAS/PAS_5perc_either_ChimpCoordChimpUsage.sort.bed

Metadata:

Metadata=read.table("../data/Peaks_5perc/Peaks_5perc_either_bothUsage.txt",header=T,stringsAsFactors = F)  %>% inner_join(strandinfo, by="PAS")

write.table(Metadata,"../data/PAS/PAS_5perc_either_HumanCoord_BothUsage_meta.txt",col.names = T, row.names = F, quote = F, sep="\t")

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] workflowr_1.6.0 forcats_0.3.0   stringr_1.3.1   dplyr_0.8.0.1  
 [5] purrr_0.3.2     readr_1.3.1     tidyr_0.8.3     tibble_2.1.1   
 [9] ggplot2_3.1.1   tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.2       cellranger_1.1.0 plyr_1.8.4       compiler_3.5.1  
 [5] pillar_1.3.1     later_0.7.5      git2r_0.26.1     tools_3.5.1     
 [9] digest_0.6.18    lubridate_1.7.4  jsonlite_1.6     evaluate_0.12   
[13] nlme_3.1-137     gtable_0.2.0     lattice_0.20-38  pkgconfig_2.0.2 
[17] rlang_0.4.0      cli_1.1.0        rstudioapi_0.10  yaml_2.2.0      
[21] haven_1.1.2      withr_2.1.2      xml2_1.2.0       httr_1.3.1      
[25] knitr_1.20       hms_0.4.2        generics_0.0.2   fs_1.3.1        
[29] rprojroot_1.3-2  grid_3.5.1       tidyselect_0.2.5 glue_1.3.0      
[33] R6_2.3.0         readxl_1.1.0     rmarkdown_1.10   modelr_0.1.2    
[37] magrittr_1.5     whisker_0.3-2    backports_1.1.2  scales_1.0.0    
[41] promises_1.0.1   htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0
[45] colorspace_1.3-2 httpuv_1.4.5     stringi_1.2.4    lazyeval_0.2.1  
[49] munsell_0.5.0    broom_0.5.1      crayon_1.3.4

From peak to PAS

Briana Mittleman

1/9/2020

Human

chimp:

Metadata: