Verify first intron result

Last updated: 2019-06-20

Checks: 6 0

Knit directory: apaQTL/analysis/

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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	b2def08	brimittleman	2019-06-20	first intron in sites with ss
html	5a02775	brimittleman	2019-06-18	Build site.
Rmd	078b340	brimittleman	2019-06-18	add first intron length
html	b3328b6	brimittleman	2019-06-18	Build site.
Rmd	01bc8aa	brimittleman	2019-06-18	add verify first inton res

In the previous analysis I saw that most of my intronic pas are in the first intron and skew toward the beginning of long introns. I will further explore this result here.

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(cowplot)


Attaching package: 'cowplot'

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

    ggsave

library(workflowr)

This is workflowr version 1.3.0
Run ?workflowr for help getting started

Nuclear

These are the nuclear intronic PAS

pas2intron=read.table("../data/intron_analysis/IntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand"),stringsAsFactors = F) %>% 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) %>% mutate(LengthCat=ifelse(intronLength<=3929, "first", ifelse(intronLength>3929 &intronLength<=9220, "second", ifelse(intronLength>9220 &intronLength<=24094, "third", "fourth"))))

pas2intron$LengthCat <- factor(pas2intron$LengthCat, levels=c("first", "second", "third", "fourth"))

Beginning of introns

I want to plot the absolute distance rather than the standardized distance to the 5’ ss.

ggplot(pas2intron,aes(x=distance2PAS, fill=LengthCat)) + geom_histogram(bins=100)  + facet_grid(~LengthCat) + xlim(0,5000)

Warning: Removed 6143 rows containing non-finite values (stat_bin).

Warning: Removed 8 rows containing missing values (geom_bar).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

ggplot(pas2intron,aes(x=distance2PAS, fill=LengthCat))  + facet_grid(~LengthCat) + xlim(0,5000) +  stat_ecdf(aes(col=LengthCat))

Warning: Removed 6143 rows containing non-finite values (stat_ecdf).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

First intron

This is not the correct analysis. I need to actually look at which intron from all of them.

this is the file I created to get the introns. I need to remove genes with only 1 introm.

introns=read.table("/project2/gilad/briana/apaQTL/data/intron_analysis/transcriptsMinusExons.sort.bed",stringsAsFactors = F, col.names = c("chrom", "intronStart", "intronEnd", "gene", "score", "strand")) %>% group_by(gene)  %>% filter(!grepl("hap",chrom)) %>% mutate(Intronid=ifelse(strand=="+",  1:n(),n():1), nintron=n()) %>% filter(nintron>2)

Join with PAS:

pas2intron_intron=pas2intron %>% inner_join(introns, by=c("intronStart","intronEnd","gene", "strand" ))
pas2intron_intron$Intronid=as.factor(pas2intron_intron$Intronid)


write.table(pas2intron_intron, "../data/intron_analysis/NuclearIntronPASwithWhichintron.txt", col.names = T, row.names = F, quote = F, sep="\t")

ggplot(pas2intron_intron,aes(x=Intronid)) +  geom_bar(stat="count") + labs(title="intron ID for nuclear intronic pas", x="intron ID")

Version	Author	Date
b3328b6	brimittleman	2019-06-18

summary(pas2intron_intron$Intronid)

   1    2    3    4    5    6    7    8    9   10   11   12   13   14   15 
3147 2111 1585 1278  896  725  633  503  432  384  287  238  188  178  145 
  16   17   18   19   20   21   22   23   24   25   26   27   28   29   30 
 119  113  106   83   71   56   63   48   58   40   36   31   18   14    9 
  31   32   33   34   35   36   37   38   39   40   41   42   43   44   45 
  11   12   13    6    3    6    5   10    7   11    9    8    5    9    6 
  46   47   48   49   50   51   52   53   55   57   58   59   60   64   66 
   2    3    1    1    6    4    7    4    1    3    6    3    1    1    5 
  67   68   69   70   72   73   74   76   77   79   85   88   89   90   94 
   4    4    5    1    3    2    1    1    2    1    1    3    2    1    2 
  96  160  165 
   2    1    2

I want to see if the usage is the same over this:

pas2intron_intron_usagecat= pas2intron_intron %>% mutate(UsageCat=ifelse(meanUsage<=.1, "<.1", ifelse(meanUsage>.1 &meanUsage<=.2, "<.2", ifelse(meanUsage>.2 &meanUsage<=.3, "<.3", ">.3"))))
pas2intron_intron_usagecat$Intronid=as.numeric(as.character(pas2intron_intron_usagecat$Intronid))

ggplot(pas2intron_intron_usagecat,aes(x=Intronid, fill=UsageCat)) +  geom_bar(stat="count") + labs(title="intron ID for nuclear intronic pas", x="intron ID") + facet_grid(~UsageCat)+ xlim(0,10)

Warning: Removed 2108 rows containing non-finite values (stat_count).

Warning: Removed 4 rows containing missing values (geom_bar).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

Maybe by the number of introns?

summary(pas2intron_intron_usagecat$nintron)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   3.00    6.00   11.00   14.41   18.00  171.00

pas2intron_intron_usagecat_introncat= pas2intron_intron_usagecat %>% mutate(IntronCat=ifelse(nintron<=6, "first (<6)", ifelse(nintron>6 &nintron<=11, "second (6-11)", ifelse(nintron>11 &nintron<=18, "third (11-18)", "fourth (>18)"))))

pas2intron_intron_usagecat_introncat$IntronCat <- factor(pas2intron_intron_usagecat_introncat$IntronCat, levels=c("first (<6)", "second (6-11)", "third (11-18)", "fourth (>18)"))

ggplot(pas2intron_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) +  geom_bar(stat="count") + labs(title="intron ID for nuclear intronic pas", x="intron ID") + facet_grid(~IntronCat) + xlim(0,10)

Warning: Removed 2108 rows containing non-finite values (stat_count).

Warning: Removed 3 rows containing missing values (geom_bar).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

nuclear_cdf=ggplot(pas2intron_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) +  stat_ecdf(aes(col=IntronCat)) + labs(title="intron ID for Nuclear intronic pas", x="intron ID") + xlim(0,10)+ geom_vline(xintercept = 2)

Total

First intron

pas2intronTot=read.table("../data/intron_analysis/TotalIntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand"),stringsAsFactors = F) %>% 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) %>%  mutate(LengthCat=ifelse(intronLength<=3785, "first", ifelse(intronLength>3785 &intronLength<=8872, "second", ifelse(intronLength>8872 &intronLength<=22928, "third", "fourth"))))

pas2intronTot$LengthCat <- factor(pas2intronTot$LengthCat, levels=c("first", "second", "third", "fourth"))
pas2intronTot_intron=pas2intronTot %>% inner_join(introns, by=c("intronStart","intronEnd","gene", "strand" ))

write.table(pas2intronTot_intron, "../data/intron_analysis/TotalIntronPASwithWhichintron.txt", col.names = T, row.names = F, quote = F, sep="\t")

summary(pas2intronTot_intron$nintron)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   3.00    6.00   11.00   14.62   18.00  171.00

pas2intronTot_intron_usagecat_introncat= pas2intronTot_intron %>% mutate(IntronCat=ifelse(nintron<=6, "first (<6)", ifelse(nintron>6 &nintron<=11, "second (6-11)", ifelse(nintron>11 &nintron<=18, "third (11-18)", "fourth (>18)"))))

ggplot(pas2intronTot_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) +  geom_bar(stat="count") + labs(title="intron ID for Total intronic pas", x="intron ID") + facet_grid(~IntronCat) + xlim(0,10)

Warning: Removed 1327 rows containing non-finite values (stat_count).

Warning: Removed 3 rows containing missing values (geom_bar).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

totalcdf=ggplot(pas2intronTot_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) +  stat_ecdf(aes(col=IntronCat)) + labs(title="intron ID for Total intronic pas", x="intron ID") + xlim(0,10) + geom_vline(xintercept = 2)

Both fracitons

Plot both:

pas2intronTot_intron_usagecat_introncat_frac=pas2intronTot_intron_usagecat_introncat %>% mutate(fraction="Total") %>% select(Intronid,IntronCat,fraction)

pas2intron_intron_usagecat_introncat_frac=pas2intron_intron_usagecat_introncat%>% mutate(fraction="Nuclear") %>% select(Intronid,IntronCat,fraction)

intronidboth=bind_rows(pas2intronTot_intron_usagecat_introncat_frac,pas2intron_intron_usagecat_introncat_frac)

Warning in bind_rows_(x, .id): binding character and factor vector,
coercing into character vector

ggplot(intronidboth,aes(x=Intronid)) +  stat_ecdf(aes(col=fraction)) + labs(title="intron ID for intronic pas", x="intron ID") + xlim(0,10) + facet_grid(~IntronCat)

Warning: Removed 3435 rows containing non-finite values (stat_ecdf).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

plot_grid(nuclear_cdf,totalcdf)

Warning: Removed 2108 rows containing non-finite values (stat_ecdf).

Warning: Removed 1327 rows containing non-finite values (stat_ecdf).

Version	Author	Date
b3328b6	brimittleman	2019-06-18

Usage in both fractions.

TotalIntronicUsage=pas2intronTot_intron_usagecat_introncat %>% mutate(fraction="Total") %>% select(meanUsage,fraction)

NuclearIntronicUsage=pas2intron_intron_usagecat_introncat%>% mutate(fraction="Nuclear") %>% select(meanUsage,fraction)

bothIntronicUsage=bind_rows(TotalIntronicUsage,NuclearIntronicUsage)

ggplot(bothIntronicUsage, aes(x=meanUsage))  +  stat_ecdf(aes(col=fraction))

Version	Author	Date
b3328b6	brimittleman	2019-06-18

Final plot:
first intron (conditioned on the intron being > 2KB) shows no signal (plotting the first 2kb only)

firstintron_nuclear=pas2intron_intron_usagecat_introncat %>% filter(Intronid==1,intronLength>2000) 

firstintron_total=pas2intronTot_intron_usagecat_introncat %>% filter(Intronid==1,intronLength>2000)

ggplot(firstintron_nuclear,aes(x=distance2PAS, fill=LengthCat)) + geom_histogram(bins=50) +xlim(0,2000) + facet_grid(~LengthCat)+ labs(title="Nuclear intronic PAS in first intron (3025)")

Warning: Removed 2280 rows containing non-finite values (stat_bin).

Warning: Removed 8 rows containing missing values (geom_bar).

Version	Author	Date
5a02775	brimittleman	2019-06-18

ggplot(firstintron_total,aes(x=distance2PAS, fill=LengthCat)) + geom_histogram(bins=50) +xlim(0,2000) + facet_grid(~LengthCat) + labs(title="Total intronic PAS in first intron (1804)")

Warning: Removed 1277 rows containing non-finite values (stat_bin).

Warning: Removed 8 rows containing missing values (geom_bar).

Version	Author	Date
5a02775	brimittleman	2019-06-18

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_1.3.0 cowplot_0.9.4   forcats_0.3.0   stringr_1.3.1  
 [5] dplyr_0.8.0.1   purrr_0.3.2     readr_1.3.1     tidyr_0.8.3    
 [9] tibble_2.1.1    ggplot2_3.1.1   tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0       cellranger_1.1.0 pillar_1.3.1     compiler_3.5.1  
 [5] git2r_0.25.2     plyr_1.8.4       tools_3.5.1      digest_0.6.18   
 [9] lubridate_1.7.4  jsonlite_1.6     evaluate_0.12    nlme_3.1-137    
[13] gtable_0.2.0     lattice_0.20-38  pkgconfig_2.0.2  rlang_0.3.1     
[17] cli_1.0.1        rstudioapi_0.10  yaml_2.2.0       haven_1.1.2     
[21] withr_2.1.2      xml2_1.2.0       httr_1.3.1       knitr_1.20      
[25] hms_0.4.2        generics_0.0.2   fs_1.2.6         rprojroot_1.3-2 
[29] grid_3.5.1       tidyselect_0.2.5 glue_1.3.0       R6_2.3.0        
[33] readxl_1.1.0     rmarkdown_1.10   reshape2_1.4.3   modelr_0.1.2    
[37] magrittr_1.5     whisker_0.3-2    backports_1.1.2  scales_1.0.0    
[41] htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0 colorspace_1.3-2
[45] labeling_0.3     stringi_1.2.4    lazyeval_0.2.1   munsell_0.5.0   
[49] broom_0.5.1      crayon_1.3.4

Verify first intron result

Briana Mittleman

6/18/2019

Nuclear

Beginning of introns

First intron

Total

First intron

Both fracitons