Comparing predicted UTRs

Last updated: 2018-11-18

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File	Version	Author	Date	Message
Rmd	3e6a944	Philipp Ross	2018-09-25	updated utr comparison
html	3e6a944	Philipp Ross	2018-09-25	updated utr comparison
html	c5562e7	Philipp Ross	2018-09-25	updated utr comparison
Rmd	fa4fca8	Philipp Ross	2018-09-25	added homopolymer analysis
Rmd	1e6d9bb	Philipp Ross	2018-09-24	comparing UTRs
html	1e6d9bb	Philipp Ross	2018-09-24	comparing UTRs

Comparing different UTR and TSS predictions

Since we were able to predict both UTRs and TSSs using our data, we wanted to know how our predictions compared to previously published predictions. Here, we compare the UTRs predicted in Caro et al. and Adjalley et al..

What we see is that although there are some large deviations, for the majority of 5UTR and TSS predictions, the results are not very different with a mean hovering around zero base pairs of difference between the start positions of our predicted 5’ UTRs and TSS and those that were previously published.

First, let’s import our 5UTR data:

library(org.Pf.plasmo.db)
aliases <- tibble::as_tibble(data.frame(org.Pf.plasmoALIAS2ORF))

utrs <- tibble::as_tibble(rtracklayer::import.gff("../output/final_utrs/final_5utrs_3d7.gff"))
utrs$Parent <- unlist(utrs$Parent)

Comparing to Caro et al.

# Comparing our UTR estimates to the Derisi predictions

derisi1 <- tibble::as_tibble(rtracklayer::import.bed("../data/compare_utrs/GSM1410291_UTRs_1.bed"))
derisi2 <- tibble::as_tibble(rtracklayer::import.bed("../data/compare_utrs/GSM1410292_UTRs_2.bed"))
derisi3 <- tibble::as_tibble(rtracklayer::import.bed("../data/compare_utrs/GSM1410293_UTRs_3.bed"))
derisi4 <- tibble::as_tibble(rtracklayer::import.bed("../data/compare_utrs/GSM1410294_UTRs_4.bed"))
derisi5 <- tibble::as_tibble(rtracklayer::import.bed("../data/compare_utrs/GSM1410295_UTRs_5.bed"))

fix_derisi_utrs <- function(set) {
  set$name <- stringi::stri_replace_last(set$name,replacement=" ",regex="_")
  set <- set %>% tidyr::separate(name,into = c("gene_id","type"), sep =" ")
  set$gene_id <- toupper(set$gene_id)
  out <- dplyr::inner_join(set, aliases, by=c("gene_id"="alias_symbol"))
  return(out)
}

derisi1 <- fix_derisi_utrs(derisi1)
derisi2 <- fix_derisi_utrs(derisi2)
derisi3 <- fix_derisi_utrs(derisi3)
derisi4 <- fix_derisi_utrs(derisi4)
derisi5 <- fix_derisi_utrs(derisi5)

Timepoint 1

tmp1 <- dplyr::select(derisi1, gene_id.y, width)
tmp2 <- dplyr::select(utrs, Parent, width)
compare_derisi <- dplyr::inner_join(tmp1,tmp2,by=c("gene_id.y"="Parent"))
rm(tmp1,tmp2)

g <- ggplot(compare_derisi,aes(width.x,width.y)) + 
  geom_point() + 
  geom_abline(color="red") +
  xlab("") + 
  ylab("") 

cowplot::save_plot(filename="../output/compare/derisi_scatter_1.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_scatter_1.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-4-1.png:

Version	Author	Date
3e6a944	Philipp Ross	2018-09-25
1e6d9bb	Philipp Ross	2018-09-24

g <- ggplot(compare_derisi,aes(width.x-width.y)) + 
  geom_histogram(color="grey70") +
  xlab("") + 
  ylab("")

cowplot::save_plot(filename="../output/compare/derisi_histogram_1.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_histogram_1.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-4-2.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

cor.test(compare_derisi$width.x,compare_derisi$width.y)


    Pearson's product-moment correlation

data:  compare_derisi$width.x and compare_derisi$width.y
t = 44.624, df = 7619, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.4372115 0.4728149
sample estimates:
      cor 
0.4551951

compare_derisi %>% dplyr::mutate(diff=width.x-width.y) %>% summary()

  gene_id.y            width.x          width.y          diff         
 Length:7621        Min.   :   0.0   Min.   :   2   Min.   :-5101.00  
 Class :character   1st Qu.: 221.0   1st Qu.: 281   1st Qu.: -328.00  
 Mode  :character   Median : 498.0   Median : 513   Median :  -37.00  
                    Mean   : 610.5   Mean   : 674   Mean   :  -63.45  
                    3rd Qu.: 810.0   3rd Qu.: 895   3rd Qu.:  196.00  
                    Max.   :6810.0   Max.   :5404   Max.   : 5601.00

Timepoint 2

tmp1 <- dplyr::select(derisi2, gene_id.y, width)
tmp2 <- dplyr::select(utrs, Parent, width)
compare_derisi <- dplyr::inner_join(tmp1,tmp2,by=c("gene_id.y"="Parent"))
rm(tmp1,tmp2)

g <- ggplot(compare_derisi,aes(width.x,width.y)) + 
  geom_point() + 
  geom_abline(color="red") +
  xlab("") + 
  ylab("") 

cowplot::save_plot(filename="../output/compare/derisi_scatter_2.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_scatter_2.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-5-1.png:

Version	Author	Date
3e6a944	Philipp Ross	2018-09-25
1e6d9bb	Philipp Ross	2018-09-24

g <- ggplot(compare_derisi,aes(width.x-width.y)) + 
  geom_histogram(color="grey70") +
  xlab("") + 
  ylab("")

cowplot::save_plot(filename="../output/compare/derisi_histogram_2.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_histogram_2.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-5-2.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

cor.test(compare_derisi$width.x,compare_derisi$width.y)


    Pearson's product-moment correlation

data:  compare_derisi$width.x and compare_derisi$width.y
t = 39.839, df = 7926, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.3899543 0.4266379
sample estimates:
     cor 
0.408461

compare_derisi %>% dplyr::mutate(diff=width.x-width.y) %>% summary()

  gene_id.y            width.x          width.y            diff        
 Length:7928        Min.   :   0.0   Min.   :   2.0   Min.   :-5111.0  
 Class :character   1st Qu.: 146.0   1st Qu.: 283.0   1st Qu.: -418.0  
 Mode  :character   Median : 428.0   Median : 518.0   Median :  -93.0  
                    Mean   : 508.4   Mean   : 675.7   Mean   : -167.4  
                    3rd Qu.: 690.2   3rd Qu.: 897.0   3rd Qu.:  120.0  
                    Max.   :8149.0   Max.   :5404.0   Max.   : 7725.0

Timepoint 3

tmp1 <- dplyr::select(derisi3, gene_id.y, width)
tmp2 <- dplyr::select(utrs, Parent, width)
compare_derisi <- dplyr::inner_join(tmp1,tmp2,by=c("gene_id.y"="Parent"))
rm(tmp1,tmp2)

g <- ggplot(compare_derisi,aes(width.x,width.y)) + 
  geom_point() + 
  geom_abline(color="red") +
  xlab("") + 
  ylab("") 

cowplot::save_plot(filename="../output/compare/derisi_scatter_3.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_scatter_3.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-6-1.png:

Version	Author	Date
3e6a944	Philipp Ross	2018-09-25
1e6d9bb	Philipp Ross	2018-09-24

g <- ggplot(compare_derisi,aes(width.x-width.y)) + 
  geom_histogram(color="grey70") +
  xlab("") + 
  ylab("")

cowplot::save_plot(filename="../output/compare/derisi_histogram_3.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_histogram_3.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-6-2.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

cor.test(compare_derisi$width.x,compare_derisi$width.y)


    Pearson's product-moment correlation

data:  compare_derisi$width.x and compare_derisi$width.y
t = 40.612, df = 7201, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.4127160 0.4503005
sample estimates:
      cor 
0.4316956

compare_derisi %>% dplyr::mutate(diff=width.x-width.y) %>% summary()

  gene_id.y            width.x          width.y          diff        
 Length:7203        Min.   :   0.0   Min.   :   2   Min.   :-5111.0  
 Class :character   1st Qu.: 346.5   1st Qu.: 289   1st Qu.: -268.0  
 Mode  :character   Median : 541.0   Median : 528   Median :    6.0  
                    Mean   : 655.6   Mean   : 689   Mean   :  -33.4  
                    3rd Qu.: 816.5   3rd Qu.: 912   3rd Qu.:  233.5  
                    Max.   :8229.0   Max.   :5404   Max.   : 7805.0

Timepoint 4

tmp1 <- dplyr::select(derisi4, gene_id.y, width)
tmp2 <- dplyr::select(utrs, Parent, width)
compare_derisi <- dplyr::inner_join(tmp1,tmp2,by=c("gene_id.y"="Parent"))
rm(tmp1,tmp2)

g <- ggplot(compare_derisi,aes(width.x,width.y)) + 
  geom_point() + 
  geom_abline(color="red") +
  xlab("") + 
  ylab("") 

cowplot::save_plot(filename="../output/compare/derisi_scatter_4.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_scatter_4.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-7-1.png:

Version	Author	Date
3e6a944	Philipp Ross	2018-09-25
1e6d9bb	Philipp Ross	2018-09-24

g <- ggplot(compare_derisi,aes(width.x-width.y)) + 
  geom_histogram(color="grey70") +
  xlab("") + 
  ylab("")

cowplot::save_plot(filename="../output/compare/derisi_histogram_4.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_histogram_4.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-7-2.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

cor.test(compare_derisi$width.x,compare_derisi$width.y)


    Pearson's product-moment correlation

data:  compare_derisi$width.x and compare_derisi$width.y
t = 39.132, df = 7197, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.3996269 0.4377261
sample estimates:
      cor 
0.4188608

compare_derisi %>% dplyr::mutate(diff=width.x-width.y) %>% summary()

  gene_id.y            width.x          width.y            diff          
 Length:7199        Min.   :   0.0   Min.   :   2.0   Min.   :-5111.000  
 Class :character   1st Qu.: 340.0   1st Qu.: 287.0   1st Qu.: -261.500  
 Mode  :character   Median : 549.0   Median : 523.0   Median :   15.000  
                    Mean   : 674.9   Mean   : 682.7   Mean   :   -7.868  
                    3rd Qu.: 855.5   3rd Qu.: 902.0   3rd Qu.:  262.500  
                    Max.   :7030.0   Max.   :5404.0   Max.   : 5821.000

Timepoint 5

tmp1 <- dplyr::select(derisi5, gene_id.y, width)
tmp2 <- dplyr::select(utrs, Parent, width)
compare_derisi <- dplyr::inner_join(tmp1,tmp2,by=c("gene_id.y"="Parent"))
rm(tmp1,tmp2)

g <- ggplot(compare_derisi,aes(width.x,width.y)) + 
  geom_point() + 
  geom_abline(color="red") +
  xlab("") + 
  ylab("") 

cowplot::save_plot(filename="../output/compare/derisi_scatter_5.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_scatter_5.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-8-1.png:

Version	Author	Date
3e6a944	Philipp Ross	2018-09-25
1e6d9bb	Philipp Ross	2018-09-24

g <- ggplot(compare_derisi,aes(width.x-width.y)) + 
  geom_histogram(color="grey70") +
  xlab("") + 
  ylab("")

cowplot::save_plot(filename="../output/compare/derisi_histogram_5.png",plot=g)
cowplot::save_plot(filename="../output/compare/derisi_histogram_5.svg",plot=g)
print(g)

Expand here to see past versions of unnamed-chunk-8-2.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

cor.test(compare_derisi$width.x,compare_derisi$width.y)


    Pearson's product-moment correlation

data:  compare_derisi$width.x and compare_derisi$width.y
t = 29.152, df = 8625, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.2801573 0.3185779
sample estimates:
     cor 
0.299489

compare_derisi %>% dplyr::mutate(diff=width.x-width.y) %>% summary()

  gene_id.y            width.x           width.y            diff        
 Length:8627        Min.   :    0.0   Min.   :   2.0   Min.   :-5111.0  
 Class :character   1st Qu.:    0.0   1st Qu.: 277.0   1st Qu.: -718.0  
 Mode  :character   Median :    0.0   Median : 508.0   Median : -415.0  
                    Mean   :  164.4   Mean   : 660.9   Mean   : -496.4  
                    3rd Qu.:   63.0   3rd Qu.: 877.0   3rd Qu.: -189.0  
                    Max.   :13050.0   Max.   :5404.0   Max.   :12541.0

Comparing to Adjalley et al.

# Comparing our UTR estimates to the Adjalley predictions
adjalley <- tibble::as_tibble(rtracklayer::import.gff("../data/compare_utrs/sorted_Adjalley_Chabbert_TSSs.gff"))

for (i in 1:8) {
  adjalley_filtered <- adjalley %>%
    dplyr::mutate(position=(start+end)/2) %>%
    dplyr::filter(FilterSize>i)
  tmp1 <- dplyr::select(adjalley_filtered, AssignedFeat, position)
  tmp2 <- dplyr::select(utrs, Parent, start)
  compare_adjalley <- dplyr::inner_join(tmp1,tmp2,by=c("AssignedFeat"="Parent"))
  compare_adjalley %>% dplyr::mutate(diff=position-start) %>% summary() %>% print()
  g <- ggplot(compare_adjalley,aes(position-start)) + 
    geom_histogram(color="grey70") +
    xlab("") + 
    ylab("")
  cowplot::save_plot(filename=paste0("../output/compare/adjalley_histogram_",i,".png"),plot=g)
  cowplot::save_plot(filename=paste0("../output/compare/adjalley_histogram_",i,".svg"),plot=g)
  print(g)
}

 AssignedFeat          position           start              diff        
 Length:36663       Min.   :  40331   Min.   :  43094   Min.   :-4992.0  
 Class :character   1st Qu.: 428840   1st Qu.: 427513   1st Qu.: -222.0  
 Mode  :character   Median : 836668   Median : 836849   Median :  292.0  
                    Mean   : 963933   Mean   : 963522   Mean   :  410.9  
                    3rd Qu.:1305788   3rd Qu.:1305295   3rd Qu.: 1044.0  
                    Max.   :3253500   Max.   :3253655   Max.   :12155.0

 AssignedFeat          position           start              diff        
 Length:29055       Min.   :  41434   Min.   :  43094   Min.   :-4967.0  
 Class :character   1st Qu.: 421766   1st Qu.: 421138   1st Qu.: -262.0  
 Mode  :character   Median : 824344   Median : 823912   Median :  328.5  
                    Mean   : 947811   Mean   : 947361   Mean   :  449.5  
                    3rd Qu.:1282446   3rd Qu.:1282646   3rd Qu.: 1169.5  
                    Max.   :3236321   Max.   :3231222   Max.   :12155.0

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Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

 AssignedFeat          position           start              diff        
 Length:29055       Min.   :  41434   Min.   :  43094   Min.   :-4967.0  
 Class :character   1st Qu.: 421766   1st Qu.: 421138   1st Qu.: -262.0  
 Mode  :character   Median : 824344   Median : 823912   Median :  328.5  
                    Mean   : 947811   Mean   : 947361   Mean   :  449.5  
                    3rd Qu.:1282446   3rd Qu.:1282646   3rd Qu.: 1169.5  
                    Max.   :3236321   Max.   :3231222   Max.   :12155.0

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Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

 AssignedFeat          position           start              diff        
 Length:18268       Min.   :  41434   Min.   :  43094   Min.   :-4967.0  
 Class :character   1st Qu.: 417702   1st Qu.: 417063   1st Qu.: -288.1  
 Mode  :character   Median : 810819   Median : 811370   Median :  295.0  
                    Mean   : 948485   Mean   : 948096   Mean   :  388.8  
                    3rd Qu.:1286032   3rd Qu.:1286107   3rd Qu.: 1087.0  
                    Max.   :3207218   Max.   :3207055   Max.   :12155.0

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Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

 AssignedFeat          position           start              diff        
 Length:10086       Min.   :  41434   Min.   :  43094   Min.   :-4957.5  
 Class :character   1st Qu.: 417660   1st Qu.: 417063   1st Qu.: -247.5  
 Mode  :character   Median : 811348   Median : 811370   Median :  291.0  
                    Mean   : 940319   Mean   : 939934   Mean   :  385.0  
                    3rd Qu.:1284996   3rd Qu.:1284735   3rd Qu.: 1034.4  
                    Max.   :3207218   Max.   :3207055   Max.   : 6628.0

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Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

 AssignedFeat          position           start              diff        
 Length:4644        Min.   :  41434   Min.   :  43094   Min.   :-4948.5  
 Class :character   1st Qu.: 397119   1st Qu.: 397397   1st Qu.: -259.5  
 Mode  :character   Median : 766111   Median : 765911   Median :  244.8  
                    Mean   : 934627   Mean   : 934337   Mean   :  289.9  
                    3rd Qu.:1295386   3rd Qu.:1293965   3rd Qu.:  878.0  
                    Max.   :3207218   Max.   :3207055   Max.   : 6100.0

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Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

 AssignedFeat          position           start              diff        
 Length:1665        Min.   :  58482   Min.   :  59727   Min.   :-4948.5  
 Class :character   1st Qu.: 369837   1st Qu.: 368586   1st Qu.: -258.0  
 Mode  :character   Median : 792528   Median : 792937   Median :  227.5  
                    Mean   : 968848   Mean   : 968578   Mean   :  270.5  
                    3rd Qu.:1357263   3rd Qu.:1357159   3rd Qu.:  845.0  
                    Max.   :2889297   Max.   :2888660   Max.   : 6100.0

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Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

 AssignedFeat          position           start              diff        
 Length:511         Min.   :  83962   Min.   :  83928   Min.   :-4615.5  
 Class :character   1st Qu.: 319338   1st Qu.: 318727   1st Qu.: -286.2  
 Mode  :character   Median : 758262   Median : 758556   Median :  181.0  
                    Mean   : 923067   Mean   : 922854   Mean   :  212.9  
                    3rd Qu.:1302403   3rd Qu.:1301308   3rd Qu.:  740.0  
                    Max.   :2889297   Max.   :2888660   Max.   : 4699.5

Expand here to see past versions of unnamed-chunk-9-7.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

Expand here to see past versions of unnamed-chunk-9-8.png:

Version	Author	Date
1e6d9bb	Philipp Ross	2018-09-24

rm(tmp1,tmp2)

Session information

sessionInfo()

R version 3.5.0 (2018-04-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Gentoo/Linux

Matrix products: default
BLAS: /usr/local/lib64/R/lib/libRblas.so
LAPACK: /usr/local/lib64/R/lib/libRlapack.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] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] bindrcpp_0.2.2                       
 [2] gdtools_0.1.7                        
 [3] BSgenome.Pfalciparum.PlasmoDB.v24_1.0
 [4] BSgenome_1.48.0                      
 [5] rtracklayer_1.40.6                   
 [6] Biostrings_2.48.0                    
 [7] XVector_0.20.0                       
 [8] GenomicRanges_1.32.7                 
 [9] GenomeInfoDb_1.16.0                  
[10] org.Pf.plasmo.db_3.6.0               
[11] AnnotationDbi_1.42.1                 
[12] IRanges_2.14.12                      
[13] S4Vectors_0.18.3                     
[14] Biobase_2.40.0                       
[15] BiocGenerics_0.26.0                  
[16] scales_1.0.0                         
[17] cowplot_0.9.3                        
[18] magrittr_1.5                         
[19] forcats_0.3.0                        
[20] stringr_1.3.1                        
[21] dplyr_0.7.6                          
[22] purrr_0.2.5                          
[23] readr_1.1.1                          
[24] tidyr_0.8.1                          
[25] tibble_1.4.2                         
[26] ggplot2_3.0.0                        
[27] tidyverse_1.2.1                      

loaded via a namespace (and not attached):
 [1] nlme_3.1-137                bitops_1.0-6               
 [3] matrixStats_0.54.0          lubridate_1.7.4            
 [5] bit64_0.9-7                 httr_1.3.1                 
 [7] rprojroot_1.3-2             tools_3.5.0                
 [9] backports_1.1.2             R6_2.3.0                   
[11] DBI_1.0.0                   lazyeval_0.2.1             
[13] colorspace_1.3-2            withr_2.1.2                
[15] tidyselect_0.2.4            bit_1.1-14                 
[17] compiler_3.5.0              git2r_0.23.0               
[19] cli_1.0.1                   rvest_0.3.2                
[21] xml2_1.2.0                  DelayedArray_0.6.6         
[23] labeling_0.3                digest_0.6.17              
[25] Rsamtools_1.32.3            svglite_1.2.1              
[27] rmarkdown_1.10              R.utils_2.7.0              
[29] pkgconfig_2.0.2             htmltools_0.3.6            
[31] rlang_0.2.2                 readxl_1.1.0               
[33] rstudioapi_0.8              RSQLite_2.1.1              
[35] bindr_0.1.1                 jsonlite_1.5               
[37] BiocParallel_1.14.2         R.oo_1.22.0                
[39] RCurl_1.95-4.11             GenomeInfoDbData_1.1.0     
[41] Matrix_1.2-14               Rcpp_0.12.19               
[43] munsell_0.5.0               R.methodsS3_1.7.1          
[45] stringi_1.2.4               whisker_0.3-2              
[47] yaml_2.2.0                  SummarizedExperiment_1.10.1
[49] zlibbioc_1.26.0             plyr_1.8.4                 
[51] grid_3.5.0                  blob_1.1.1                 
[53] crayon_1.3.4                lattice_0.20-35            
[55] haven_1.1.2                 hms_0.4.2                  
[57] knitr_1.20                  pillar_1.3.0               
[59] XML_3.98-1.16               glue_1.3.0                 
[61] evaluate_0.11               modelr_0.1.2               
[63] cellranger_1.1.0            gtable_0.2.0               
[65] assertthat_0.2.0            broom_0.5.0                
[67] GenomicAlignments_1.16.0    memoise_1.1.0              
[69] workflowr_1.1.1

This reproducible R Markdown analysis was created with workflowr 1.1.1