5’ Splice site strength

Last updated: 2020-02-17

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Unstaged changes:
    Modified:   analysis/ExploreNpas.Rmd
    Modified:   analysis/NuclearSpecIncludeNotTested.Rmd
    Modified:   analysis/PASdescriptiveplots.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/TSS.Rmd
    Modified:   analysis/decayAndStability.Rmd
    Modified:   analysis/miRNAdisrupt.Rmd
    Modified:   analysis/nascenttranscription.Rmd
    Modified:   analysis/nucSpecinEQTLs.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/pQTLexampleplot.Rmd
    Modified:   analysis/propeQTLs_explained.Rmd
    Modified:   analysis/version15bpfilter.Rmd
    Modified:   code/DistPAS2Sig.py
    Modified:   code/Script4NuclearQTLexamples.sh
    Modified:   code/Script4TotalQTLexamples.sh
    Modified:   code/apaQTLsnake.err
    Modified:   code/environment.yaml
    Modified:   code/run_qtlFacetBoxplots.sh
    Deleted:    code/test.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.

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File	Version	Author	Date	Message
Rmd	f4a296f	brimittleman	2020-02-17	add initial res for splice site

library(workflowr)

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

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()

I will assess the 5’ splice site strength with maxentscore to see if this can tell us anything interesting about intronic polyadenylation.

http://hollywood.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html

How to use MaxEntScan::score5ss

Each sequence must be 9 bases long. [3 bases in exon][6 bases in intron] Input sequences as a FastA file with one sequence per line (no linebreaks). Non-ACGT sequences will not be processed.

Example Fasta File

> dummy1
cagGTAAGT
> dummy2 
gagGTAAGT
> dummy3 
taaATAAGT

I assigned PAS to introns. in https://brimittleman.github.io/apaQTL/nucintronicanalysis.html

pas2intron=read.table("../data/intron_analysis/IntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand")) 

#%>% mutate(PASloc=ifelse(strand=="+", peakEnd, peakStart)) %>% dplyr::select(intronStart, intronEnd, gene, strand, PeakID, PASloc ,meanUsage) %>% mutate(intronLength=intronEnd-intronStart , distance2PAS= ifelse(strand=="+", PASloc-intronStart, intronEnd-PASloc), propIntron=distance2PAS/intronLength)

I need a file with the PAS and the 5’ splice site. For negative strand the 5’ is the end and postitive strand PAS it is the start.

postive: start= start-3 end= start + 6

negative: start= end -6 end= end + 3

mkdir ../data/splicesite

PAS_5SS_pos= pas2intron %>% filter(strand=="+") %>% mutate(start=intronStart-3, end= intronStart +6) %>% select(intronCHR, start,end, PeakID,meanUsage, strand)
PAS_5SS_neg=pas2intron %>% filter(strand=="-") %>% mutate(start=intronEnd-6, end= intronEnd +3) %>% select(intronCHR, start,end, PeakID,meanUsage, strand)
PAS_5SS_both= PAS_5SS_neg %>% bind_rows(PAS_5SS_pos)



write.table(PAS_5SS_pos, "../data/splicesite/TestPosSS.bed", col.names = F, row.names = F, quote=F, sep="\t")

write.table(PAS_5SS_neg, "../data/splicesite/TestNegSS.bed", col.names = F, row.names = F, quote=F, sep="\t")


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

Merge and sort these to get the nucleotides:

sort -k1,1 -k2,2n ../data/splicesite/AllPASSS.bed > ../data/splicesite/AllPASSS.sort.bed


#cut chr  

sed 's/^chr//' ../data/splicesite/AllPASSS.sort.bed >  ../data/splicesite/AllPASSS.sort.noChr.bed


#bedtools nuc

bedtools nuc -fi /project2/gilad/briana/genome_anotation_data/genome/Homo_sapiens.GRCh37.75.dna_sm.all.fa -bed ../data/splicesite/AllPASSS.sort.noChr.bed -seq -s > ../data/splicesite/AllPASSS.sort.Nuc.txt

This works and it flips the strand. the first 3 bases are the exon and the next 6 are the intron.

I need to turn this into a FA file. with the first 3 lower case and second 6 upper like the example. I can do this in python.

For each PAS i will have the name then the bases in the next

python splicesite2fasta.py

Score online with site and use Maximum Entropy Model.

splice result to keep every other line. Then I can join the reults with the initial bed.

python parseSSres.py

res=read.table("../data/splicesite/MaxIntResParsed.txt", col.names=c("splicesite", "maxentscore"), header=F, stringsAsFactors = F)

bothSS=read.table("../data/splicesite/AllPASSS.sort.noChr.bed", header = F, col.names = c("chr", 'start','end','PAS', "NuclearUsage", 'strand'))


bothandres=bothSS %>% bind_cols(res)

Plot usage and score:

cor.test(bothandres$NuclearUsage, bothandres$maxentscore)


    Pearson's product-moment correlation

data:  bothandres$NuclearUsage and bothandres$maxentscore
t = -3.547, df = 12534, p-value = 0.0003911
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.04914437 -0.01416833
sample estimates:
        cor 
-0.03166605

ggplot(bothandres, aes(x=maxentscore, y=NuclearUsage)) + geom_point() + geom_density2d(col="red")

Filter usage higher (25%) and score above 0

bothandres_filt= bothandres %>% filter(NuclearUsage>0.25, maxentscore>0)

ggplot(bothandres_filt, aes(x=maxentscore, y=NuclearUsage)) + geom_point() + geom_density2d(col="red") + geom_smooth(method="lm")

Does not look like there is a relationship here.

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_1.6.0

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.5 haven_1.1.2      lattice_0.20-38  colorspace_1.3-2
 [5] generics_0.0.2   htmltools_0.3.6  yaml_2.2.0       rlang_0.4.0     
 [9] later_0.7.5      pillar_1.3.1     glue_1.3.0       withr_2.1.2     
[13] modelr_0.1.2     readxl_1.1.0     plyr_1.8.4       munsell_0.5.0   
[17] gtable_0.2.0     cellranger_1.1.0 rvest_0.3.2      evaluate_0.12   
[21] labeling_0.3     knitr_1.20       httpuv_1.4.5     broom_0.5.1     
[25] Rcpp_1.0.2       promises_1.0.1   scales_1.0.0     backports_1.1.2 
[29] jsonlite_1.6     fs_1.3.1         hms_0.4.2        digest_0.6.18   
[33] stringi_1.2.4    grid_3.5.1       rprojroot_1.3-2  cli_1.1.0       
[37] tools_3.5.1      magrittr_1.5     lazyeval_0.2.1   crayon_1.3.4    
[41] whisker_0.3-2    pkgconfig_2.0.2  MASS_7.3-51.1    xml2_1.2.0      
[45] lubridate_1.7.4  assertthat_0.2.0 rmarkdown_1.10   httr_1.3.1      
[49] rstudioapi_0.10  R6_2.3.0         nlme_3.1-137     git2r_0.26.1    
[53] compiler_3.5.1

5’ Splice site strength

Briana Mittleman

2/17/2020