Last updated: 2018-08-22

workflowr checks: (Click a bullet for more information)
  • R Markdown file: up-to-date

    Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

  • Environment: empty

    Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

  • Seed: set.seed(20180801)

    The command set.seed(20180801) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

  • Session information: recorded

    Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

  • Repository version: 3a19b07

    Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

    Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
    
    Ignored files:
        Ignored:    .RData
        Ignored:    .Rhistory
        Ignored:    .Rproj.user/
    
    Untracked files:
        Untracked:  com_threeprime.Rproj
        Untracked:  data/dist_upexon/
        Untracked:  data/liftover/
        Untracked:  data/map.stats.csv
        Untracked:  data/map.stats.xlsx
    
    Unstaged changes:
        Modified:   analysis/index.Rmd
        Deleted:    comparitive_threeprime.Rproj
    
    
    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.
Expand here to see past versions:
    File Version Author Date Message
    Rmd 3a19b07 brimittleman 2018-08-22 add hg19 dist
    html d0d4599 brimittleman 2018-08-21 Build site.


I will use this analysis for QC on the orthologous peaks called in the liftover pipeline analysis.

Distance to ortho exon

I want to make sure the distances of the orthologous peaks to the nearest exon called in Bryans ortho exon files follow a similar distribution.

The orthologus exon files are in /project2/gilad/briana/genome_anotation_data/ortho_exon and the small version have just chr start end and exon name.

The ortho peak files are in /project2/gilad/briana/comparitive_threeprime/data/ortho_peaks/

I want the closest exon upstream, i will use bedtools closest:

distUpstreamexon.sh

#!/bin/bash

#SBATCH --job-name=disUpstreamexon
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=disUpstreamexon.out
#SBATCH --error=disUpstreamexon.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END


module load Anaconda3
source activate comp_threeprime_env

bedtools closest -id -D a -a /project2/gilad/briana/comparitive_threeprime/data/ortho_peaks/chimpOrthoPeaks.sort.bed  -b /project2/gilad/briana/genome_anotation_data/ortho_exon/2017_July_ortho_chimp.small.sort.bed > /project2/gilad/briana/comparitive_threeprime/data/dist_upexon/Chimp.distUpstreamexon.txt


bedtools closest -id -D a -a /project2/gilad/briana/comparitive_threeprime/data/ortho_peaks/humanOrthoPeaks.sort.bed -b /project2/gilad/briana/genome_anotation_data/ortho_exon/2017_July_ortho_human.small.sort.bed > /project2/gilad/briana/comparitive_threeprime/data/dist_upexon/Human.distUpstreamexon.txt

Import the files and plot the distances.

library(tidyverse)
── Attaching packages ──────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.0.0     ✔ purrr   0.2.5
✔ tibble  1.4.2     ✔ dplyr   0.7.6
✔ tidyr   0.8.1     ✔ stringr 1.3.1
✔ readr   1.1.1     ✔ forcats 0.3.0
── Conflicts ─────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
library(workflowr)
This is workflowr version 1.1.1
Run ?workflowr for help getting started
library(cowplot)

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

    ggsave
getwd()
[1] "/Users/bmittleman1/Documents/Gilad_lab/comparitive_threeprime/com_threeprime/analysis"
file.exists("../data/dist_upexon/Chimp.distUpstreamexon.txt")
[1] TRUE
chimp_dist=read.table("../data/dist_upexon/Chimp.distUpstreamexon.txt", col.names = c("peak_chr", "peak_start", "peak_end", "peak_name", "exon_chr", "exon_start", "exon_end", "exon_name", "dist"), stringsAsFactors = F) %>% mutate(logdis=log10(abs(dist) +1 ))

human_dist=read.table("../data/dist_upexon/Human.distUpstreamexon.txt", col.names = c("peak_chr", "peak_start", "peak_end", "peak_name", "exon_chr", "exon_start", "exon_end", "exon_name", "dist"),stringsAsFactors = F, skip=1) %>% mutate(logdis=log10(abs(dist) +1 ))
ch=ggplot(chimp_dist, aes(x=logdis)) + geom_density() + labs(x="log10 abs.value \n distance +1 ", title="Chimp distance to ortho exon")

hu=ggplot(human_dist, aes(x=logdis)) + geom_density()+ labs(x="log10 abs.value \n distance +1 ", title="Human distance to ortho exon")


plot_grid(ch, hu)

Expand here to see past versions of unnamed-chunk-4-1.png:
Version Author Date
d0d4599 brimittleman 2018-08-21

This is a good sanity check. The distributions are similar. I want to check this with the peaks from the human APAqtl study. I have the gencode exons and I will run bedtools cloests with this.

#!/bin/bash

#SBATCH --job-name=disUpstreamexon_hum
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=disUpstreamexon_hum.out
#SBATCH --error=disUpstreamexon_hum.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END


module load Anaconda3
source activate comp_threeprime_env

bedtools closest -id -D a -a /project2/gilad/briana/comparitive_threeprime/data/extra_anno/human_hg19_filteredPeaks.bed -b /project2/gilad/briana/comparitive_threeprime/data/extra_anno/gencode.hg19.v19.exons.bed > /project2/gilad/briana/comparitive_threeprime/data/dist_upexon/hg19.humanpeaks.distUpstreamexon.txt

update these files to remove the tab at the end.

hg19_dist=read.table("../data/dist_upexon/hg19.humanpeaks.distUpstreamexon.txt", col.names = c("peak_chr", "peak_start", "peak_end", "peak_cov","peak_strand", "peak_score", "exon_chr", "exon_start", "exon_end", "exon_name", "exon_score", "exon_strand", "dist"),stringsAsFactors = F, skip=1) %>% mutate(logdis=log10(abs(dist) +1 ))

ggplot(hg19_dist, aes(x=logdis)) + geom_density()+ labs(x="log10 abs.value \n distance +1 ", title="Hg19 peaks dist to upstream exon")

Session information

sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] bindrcpp_0.2.2  cowplot_0.9.3   workflowr_1.1.1 forcats_0.3.0  
 [5] stringr_1.3.1   dplyr_0.7.6     purrr_0.2.5     readr_1.1.1    
 [9] tidyr_0.8.1     tibble_1.4.2    ggplot2_3.0.0   tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.4  haven_1.1.2       lattice_0.20-35  
 [4] colorspace_1.3-2  htmltools_0.3.6   yaml_2.1.19      
 [7] rlang_0.2.1       R.oo_1.22.0       pillar_1.3.0     
[10] glue_1.3.0        withr_2.1.2       R.utils_2.6.0    
[13] modelr_0.1.2      readxl_1.1.0      bindr_0.1.1      
[16] plyr_1.8.4        munsell_0.5.0     gtable_0.2.0     
[19] cellranger_1.1.0  rvest_0.3.2       R.methodsS3_1.7.1
[22] evaluate_0.11     labeling_0.3      knitr_1.20       
[25] broom_0.5.0       Rcpp_0.12.18      scales_0.5.0     
[28] backports_1.1.2   jsonlite_1.5      hms_0.4.2        
[31] digest_0.6.15     stringi_1.2.4     grid_3.5.1       
[34] rprojroot_1.3-2   cli_1.0.0         tools_3.5.1      
[37] magrittr_1.5      lazyeval_0.2.1    crayon_1.3.4     
[40] whisker_0.3-2     pkgconfig_2.0.1   xml2_1.2.0       
[43] lubridate_1.7.4   assertthat_0.2.0  rmarkdown_1.10   
[46] httr_1.3.1        rstudioapi_0.7    R6_2.2.2         
[49] nlme_3.1-137      git2r_0.23.0      compiler_3.5.1   

This reproducible R Markdown analysis was created with workflowr 1.1.1