Last updated: 2020-02-11

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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/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.

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
Rmd f0b588f brimittleman 2020-02-11 add write out
html ad502c6 brimittleman 2020-02-04 Build site.
Rmd ee3c3a8 brimittleman 2020-02-04 add base comp analysis around PAS

I will test the base composition for the 20 bases around each PAS. I will get the sequences then make logo plots.

library(stringr)
library(cowplot)
Loading required package: ggplot2

Attaching package: 'cowplot'
The following object is masked from 'package:ggplot2':

    ggsave
require(ggseqlogo)
Loading required package: ggseqlogo
library(RColorBrewer)
library(workflowr)
This is workflowr version 1.6.0
Run ?workflowr for help getting started
options(scipen = 999)
library(tidyverse)
── Attaching packages ───────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ tibble  2.1.1       ✔ purrr   0.3.2  
✔ tidyr   0.8.3       ✔ dplyr   0.8.0.1
✔ readr   1.3.1       ✔ forcats 0.3.0  
── Conflicts ──────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter()   masks stats::filter()
✖ cowplot::ggsave() masks ggplot2::ggsave()
✖ dplyr::lag()      masks stats::lag()
cs1 = make_col_scheme(chars=c('A', 'T', 'C', 'G', 'N'), groups=c('A', 'T', 'C', 'G', 'N'), cols=c( "#1B9E77", "#D95F02" ,"#7570B3" ,"#E7298A", "#66A61E"))

I will add 10 to the end and subtract 10 from the end to get the 20 basepairs.

PAS=read.table("../data/PAS/APAPAS_GeneLocAnno.5perc.bed", stringsAsFactors = F, col.names=c("chr","start","end","name","score", "strand")) %>% 
  mutate(newStart=end-10,newEnd=end+10,len=newEnd-newStart)%>%
  select(chr, newStart, newEnd, name, score, strand)
mkdir ../data/BaseComp
write.table(PAS,"../data/BaseComp/PAS_regions.txt", col.names = F,row.names = F, quote = F,sep="\t")

Now use bedtools nuc to get the sequence.

bedtools nuc -s -seq -fi /project2/gilad/briana/genome_anotation_data/genome/Homo_sapiens.GRCh37.75.dna_sm.all.fa -bed ../data/BaseComp/PAS_regions.txt > ../data/BaseComp/PAS_regions_seq.txt

Results:

PASseq=read.table("../data/BaseComp/PAS_regions_seq.txt", col.names = c(colnames(PAS),"AT",'GC','As','Cs','Gs','Ts','N',"other","length","seq")) %>% 
  mutate(seqUP=toupper(seq))

Seqs=PASseq$seqUP

I will start by making a logo for all of this.

lngth=c()
for (i in Seqs){
  lngth=c(lngth, str_length(i))
}

plot(lngth)

Version Author Date
ad502c6 brimittleman 2020-02-04 
ggseqlogo(Seqs, col_scheme=cs1, method = 'prob')

Version Author Date
ad502c6 brimittleman 2020-02-04

I can seperate these by those identified in the database.

Pull in closest to database. I am using the code from earlier in the workflow:

dist=read.table("../data/AnnotatedPAS/DistanceMyPAS2Anno.bed", col.names = c("chr", "start","end","myPAS", "score","strand","chr2", "start2", "end2", "anno", "score2", "strand2", "distance"),stringsAsFactors = F)
PAS_withmatch=dist %>% filter(abs(distance)<=10) %>% select(myPAS,anno) %>% unique() %>% separate(myPAS, into=c("pasNum", "geneID"), sep=":") %>% separate(geneID, into=c("gene", "loc"), sep="_")
PASseq_anno= PASseq %>% separate(name,into=c("Num", 'geneID'),sep=":") %>% mutate(inDb=ifelse(Num %in% PAS_withmatch$pasNum,"Yes","No"))

PASseq_anno_yes=PASseq_anno %>% filter(inDb=="Yes")

PASseq_anno_no=PASseq_anno %>% filter(inDb=="No")

plot_grid(p1, p2, p3, ncol = 1, align = ‘v’)

pYes=ggseqlogo(PASseq_anno_yes$seqUP, col_scheme=cs1, method = 'prob')
nNo=ggseqlogo(PASseq_anno_no$seqUP, col_scheme=cs1, method = 'prob')
plot_grid(pYes, nNo, ncol = 1, align = 'v',labels = c('PAS in DB', 'Novel PAS'))

Version Author Date
ad502c6 brimittleman 2020-02-04

Plot these by location:

PASseq_loc=PASseq_anno %>% separate(geneID, into=c("gene","loc"), sep="_")

PASseq_UTR= PASseq_loc %>% filter(loc=="utr3")

PASseq_intron= PASseq_loc %>% filter(loc=="intron")
pUTR=ggseqlogo(PASseq_UTR$seqUP, col_scheme=cs1, method = 'prob')
pIntron=ggseqlogo(PASseq_intron$seqUP, col_scheme=cs1, method = 'prob')

plot_grid(pUTR, pIntron, ncol = 1, align = 'v',labels = c('3 UTR', 'Intronic'))

Version Author Date
ad502c6 brimittleman 2020-02-04 
PASseq_UTRYes= PASseq_loc %>% filter(loc=="utr3",inDb=="Yes")
PASseq_UTRNo= PASseq_loc %>% filter(loc=="utr3",inDb=="No")

PASseq_intronYes= PASseq_loc %>% filter(loc=="intron",inDb=="Yes")
PASseq_intronNo= PASseq_loc %>% filter(loc=="intron",inDb=="No")
pUTRYes=ggseqlogo(PASseq_UTRYes$seqUP, col_scheme=cs1, method = 'prob')
pUTRNo=ggseqlogo(PASseq_UTRNo$seqUP, col_scheme=cs1, method = 'prob')
pIntronYes=ggseqlogo(PASseq_intronYes$seqUP, col_scheme=cs1, method = 'prob')
pIntronNo=ggseqlogo(PASseq_intronNo$seqUP, col_scheme=cs1, method = 'prob')

plot_grid(pUTRYes,pUTRNo, pIntronYes, pIntronNo,ncol = 2, align = 'v',labels = c('3 UTR, Yes','3 UTR, No', 'Intronic, Yes', "Intronic, No"))

Version Author Date
ad502c6 brimittleman 2020-02-04

write out seqs for use in github package:

write.table(PASseq_UTRYes, "../data/BaseComp/Compfiles_UTR_Yes.txt", col.names = T, row.names = F, quote = F)
write.table(PASseq_UTRNo, "../data/BaseComp/Compfiles_UTR_No.txt",  col.names = T, row.names = F, quote = F)
write.table(PASseq_intronYes, "../data/BaseComp/Compfiles_intron_Yes.txt", col.names = T, row.names = F, quote = F)
write.table(PASseq_intronNo, "../data/BaseComp/Compfiles_intron_No.txt", col.names = T, row.names = F, quote = F)

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      dplyr_0.8.0.1      purrr_0.3.2       
 [4] readr_1.3.1        tidyr_0.8.3        tibble_2.1.1      
 [7] tidyverse_1.2.1    workflowr_1.6.0    RColorBrewer_1.1-2
[10] ggseqlogo_0.1      cowplot_0.9.4      ggplot2_3.1.1     
[13] stringr_1.3.1     

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  xml2_1.2.0       lubridate_1.7.4 
[45] rstudioapi_0.10  assertthat_0.2.0 rmarkdown_1.10   httr_1.3.1      
[49] R6_2.3.0         nlme_3.1-137     git2r_0.26.1     compiler_3.5.1