Last updated: 2019-04-22

Checks: 6 0

Knit directory: apaQTL/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.2.0). The Report tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


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.

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.

The command set.seed(12345) 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.

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

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

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:  .DS_Store
    Untracked:  .gitignore
    Untracked:  apaQTL.Rproj
    Untracked:  code/.DS_Store
    Untracked:  data/MetaDataSequencing.xlsx
    Untracked:  docs/.DS_Store
    Untracked:  docs/~$MetaDataSequencing.xlsx

Unstaged changes:
    Modified:   analysis/mapapaQTL.Rmd
    Modified:   data/MetaDataSequencing.txt

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 851c963 brimittleman 2019-04-22 add reads against feature

In this analysis I will create the read distribution figures. These are created using deeptools. I have merged total and nuclear bam files from the read mapping pipeline. I will convert these to bigwigs in order to map the reads against features with deeptools.

Create BW files

mkdir ../data/mergedBW_byfrac
mkdir ../data/DTmatrix
mkdir ../output/dtPlots

module load Anaconda3 
source activate three-prime-env

sbatch bam2bw.sh ../data/mergedbyFracBam/Total.SamplesMerged.sort.bam ../data/mergedBW_byfrac/Total.SamplesMerged.bw sbatch bam2bw.sh ../data/mergedbyFracBam/Nuclear.SamplesMerged.sort.bam ../data/mergedBW_byfrac/Nuclear.SamplesMerged.bw

Map along gene bodies

sbatch BothFracDTPlotGeneRegions.sh


sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.1

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     

loaded via a namespace (and not attached):
 [1] workflowr_1.2.0 Rcpp_1.0.0      digest_0.6.18   rprojroot_1.3-2
 [5] backports_1.1.3 git2r_0.24.0    magrittr_1.5    evaluate_0.13  
 [9] stringi_1.3.1   fs_1.2.6        whisker_0.3-2   rmarkdown_1.11 
[13] tools_3.5.1     stringr_1.4.0   glue_1.3.0      xfun_0.5       
[17] yaml_2.2.0      compiler_3.5.1  htmltools_0.3.6 knitr_1.21