Last updated: 2020-01-30

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    Deleted:    reads_graphs.Rmd

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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 9808654 brimittleman 2019-11-14 Build site.
Rmd 79d65a0 brimittleman 2019-11-14 add averages
html 3af0253 brimittleman 2019-09-17 Build site.
Rmd f8cb7b8 brimittleman 2019-09-17 move inclusive, get numbers for paper 
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()

In this analysis I will look at the enrichment of intron pas over all PAS. I need to get the size of all intronic regions and the size of all regions. I can do this by merging the annotations.

I can use bedtools merge on

ncbiRefSeq_FormatedallAnnotation.sort.bed and the intron regions of this.

annotation=read.table("/project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefSeq_FormatedallAnnotation.sort.bed", col.names = c("chr", "start", "end", "id", "score", "strand")) %>% separate(id,into=c("loc", "gene"),sep=":")

intron=annotation %>% filter(loc=="intron") 

write.table(intron, "/project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefSeq_intron.bed", col.names = F, row.names = F,quote = F, sep="\t")

sort:

sort -k1,1 -k2,2n /project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefseq_intron.dms > /project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefseq_intron.sort.dms

sed 's/^chr//' /project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefseq_intron.sort.dms > /project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefseq_intron.sort.noCHR.bed


bedtools merge -i /project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefseq_intron.sort.noCHR.bed -s > /project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefSeq_Merged_intron.sort.bed
chroms=as.character(seq(1,22))

intronMerged=read.table("/project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefSeq_Merged_intron.sort.bed",col.names = c("chr", "start", "end")) %>% mutate(length=end-start) %>% filter(chr %in% chroms)
allMerged=read.table("/project2/gilad/briana/genome_anotation_data/RefSeq_annotations/ncbiRefSeq_Merged.FormatedallAnnotation.sort.bed" , col.names = c("chr", "start", "end")) %>% mutate(length=end-start) %>% filter(chr %in% chroms)
intronLength=sum(intronMerged$length)
totalLength=sum(allMerged$length)

N pas in intron

intronpas=read.table("../data/PAS/APAPAS_GeneLocAnno.5perc.bed", col.names = c("chr", "start", "end", "id","score", "strand")) %>% separate(id, into = c("pasnum", "geneID"), sep=":") %>% separate(geneID, into=c("gene", "loc"),sep="_") %>% filter(loc=="intron")
allPAS=read.table("../data/PAS/APAPAS_GeneLocAnno.5perc.bed")

Values:

pas_length=nrow(allPAS)/totalLength
intron_length=nrow(intronpas)/intronLength 


enrichment=intron_length/pas_length
enrichment
[1] 0.3508243

This is a 0.35 enrichment.

Average usage of these across.

UsageNuclear=read.table("../data/PAS/NuclearPASMeanUsage.txt", stringsAsFactors = F,header = T) %>% filter(meanUsage>.05) %>% separate(ID,into=c("chr", "start","end", "PASID"), sep=":") %>% separate(PASID, into=c("gene", "loc","strand","PAS"),sep="_")
Warning: Expected 4 pieces. Additional pieces discarded in 3 rows [5127,
5128, 5129].
intronpasNum= intronpas %>% mutate(PAS=paste("peak", pasnum, sep="")) %>% select(PAS)
IntronicWusage=UsageNuclear %>% filter(PAS %in% intronpasNum$PAS)

mean(IntronicWusage$meanUsage)
[1] 0.1690871

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_1.0.2       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     workflowr_1.5.0 
 [9] tools_3.5.1      digest_0.6.18    lubridate_1.7.4  jsonlite_1.6    
[13] evaluate_0.12    nlme_3.1-137     gtable_0.2.0     lattice_0.20-38 
[17] pkgconfig_2.0.2  rlang_0.4.0      cli_1.1.0        rstudioapi_0.10 
[21] yaml_2.2.0       haven_1.1.2      withr_2.1.2      xml2_1.2.0      
[25] httr_1.3.1       knitr_1.20       hms_0.4.2        generics_0.0.2  
[29] fs_1.3.1         rprojroot_1.3-2  grid_3.5.1       tidyselect_0.2.5
[33] glue_1.3.0       R6_2.3.0         readxl_1.1.0     rmarkdown_1.10  
[37] modelr_0.1.2     magrittr_1.5     whisker_0.3-2    backports_1.1.2 
[41] scales_1.0.0     promises_1.0.1   htmltools_0.3.6  rvest_0.3.2     
[45] assertthat_0.2.0 colorspace_1.3-2 httpuv_1.4.5     stringi_1.2.4   
[49] lazyeval_0.2.1   munsell_0.5.0    broom_0.5.1      crayon_1.3.4