Last updated: 2020-02-21

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Knit directory: Comparative_APA/analysis/

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Rmd 2e8ed44 brimittleman 2020-02-21 add Splice site strength 
library(workflowr)
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There is a hypothesis that increased 5’ splice site strength is assocaited with decreased usage of intronic PAS. This is relate to competition and binding of the U1 snurp. I will ask if there are differences in 5’ splcie sites for humans and chimp.

Need to be careful about orthology here. To be conservative. I will only look at regions that map downstream of an ortho exon.

First step is to map each intronic PAS to a human intron annotation.

I created a transcript minus exon file for my previos project. I will lift this file over andcheck it. I can remake it

mkdir ../data/SpliceSite  

liftOver /project2/gilad/briana/apaQTL/data/intron_analysis/transcriptsMinusExons.sort.bed  ../data/liftover_files/hg19ToHg38.over.chain.gz ../data/SpliceSite/transcriptMinusexon_hg38.bed ../data/SpliceSite/UnliftedIntron.bed

These look really good, they line up well.

Pull out intronic PAS

PAS_metaIntron=read.table("../data/PAS_doubleFilter/PAS_10perc_either_HumanCoord_BothUsage_meta_doubleFilter.txt", header = T, stringsAsFactors = F) %>% filter(loc=="intron")
PAS=read.table("../data/PAS_doubleFilter/PAS_doublefilter_either_HumanCoordHummanUsage.bed", col.names = c("chr", "start", "end", "PAS", "score", "strand"),stringsAsFactors = F) %>% semi_join(PAS_metaIntron, by="PAS")

write.table(PAS, "../data/SpliceSite/IntronicPAS_humanCoord.bed", col.names = F, row.names = F, quote = F, sep="\t")
sbatch assignPeak2Intronicregion.sh

Get the 5’ splice sites for all of these.

(lose ~800)

PAS2Intron=read.table("../data/SpliceSite/IntronincPAS2Introns_humanCoord.bed",col.names = c("IntronChr", "IntronStart", "IntronEnd", "Gene", "Score", "Strand", "PASChr", "PASStart","PASEnd", "PAS", "humanUsage", "passtrand"),stringsAsFactors = F)

Lost= PAS %>% anti_join(PAS2Intron, by="PAS")

write.table(Lost, "../data/SpliceSite/LostinIntersect.bed", col.names = F, row.names = F, quote =F, sep = "\t")

Lose some with multiple isoforms. Downstream of a gene may be an intron in one. It is probably not possible to get perfect annotation.

PAS2Intron_pos= PAS2Intron %>% filter(Strand=="+") %>% mutate(start=IntronStart-3, end= IntronStart +6) %>% select(IntronChr, start,end, PAS,humanUsage, Strand)
PAS2Intron_neg=PAS2Intron %>% filter(Strand=="-") %>% mutate(start=IntronEnd-6, end= IntronEnd +3) %>% select(IntronChr, start,end, PAS,humanUsage, Strand)
PAS_5SS_both= PAS2Intron_neg %>% bind_rows(PAS2Intron_pos)

write.table(PAS_5SS_both, "../data/SpliceSite/IntronicPAS_SS_humanCoord.bed", col.names = F, row.names = F, quote=F, sep="\t")

Sort and assign to ortho exon. I need a small amount of overlap with the human ortho exon file. This comes from Kenneth’s work. /project2/gilad/kenneth/OrthoExonPartialMapping/human.noM.gtf

Ortho exon needs to be converted to bed to intersect.

sort -k1,1 -k2,2n ../data/SpliceSite/IntronicPAS_SS_humanCoord.bed > ../data/SpliceSite/IntronicPAS_SS_humanCoord.sort.bed

Maxent scripts are in /code/MaxEntCode/fordownload
usage: perl score5.pl test5


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:
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[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_1.6.0

loaded via a namespace (and not attached):
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 [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