Last updated: 2019-04-03

Checks: 6 0

Knit directory: threeprimeseq/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.

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(12345)

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.

Session information: recorded

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

Cache: none

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

Repository version: a79791b

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:    .DS_Store
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/.DS_Store
    Ignored:    data/perm_QTL_trans_noMP_5percov/
    Ignored:    output/.DS_Store

Untracked files:
    Untracked:  KalistoAbundance18486.txt
    Untracked:  analysis/4suDataIGV.Rmd
    Untracked:  analysis/AdaptTonyExampleplots.Rmd
    Untracked:  analysis/DirectionapaQTL.Rmd
    Untracked:  analysis/EvaleQTLs.Rmd
    Untracked:  analysis/YL_QTL_test.Rmd
    Untracked:  analysis/groSeqAnalysis.Rmd
    Untracked:  analysis/ncbiRefSeq_sm.sort.mRNA.bed
    Untracked:  analysis/peaksWithMisprimming.Rmd
    Untracked:  analysis/snake.config.notes.Rmd
    Untracked:  analysis/verifyBAM.Rmd
    Untracked:  analysis/verifybam_dubs.Rmd
    Untracked:  code/PeaksToCoverPerReads.py
    Untracked:  code/strober_pc_pve_heatmap_func.R
    Untracked:  data/18486.genecov.txt
    Untracked:  data/APApeaksYL.total.inbrain.bed
    Untracked:  data/AllPeak_counts/
    Untracked:  data/ApaQTLs/
    Untracked:  data/ApaQTLs_otherPhen/
    Untracked:  data/CTCF/
    Untracked:  data/ChromHmmOverlap/
    Untracked:  data/DistTXN2Peak_genelocAnno/
    Untracked:  data/EmpiricalDists/
    Untracked:  data/ExampleQTLplot2/
    Untracked:  data/FeatureoverlapPeaks/
    Untracked:  data/GM12878.chromHMM.bed
    Untracked:  data/GM12878.chromHMM.txt
    Untracked:  data/GWAS_overlap/
    Untracked:  data/LianoglouLCL/
    Untracked:  data/LocusZoom/
    Untracked:  data/LocusZoom_Unexp/
    Untracked:  data/LocusZoom_proc/
    Untracked:  data/MatchedSnps/
    Untracked:  data/NucSpecQTL/
    Untracked:  data/NuclearApaQTLs.txt
    Untracked:  data/PeakCounts/
    Untracked:  data/PeakCounts_noMP_5perc/
    Untracked:  data/PeakCounts_noMP_genelocanno/
    Untracked:  data/PeakUsage/
    Untracked:  data/PeakUsage_noMP/
    Untracked:  data/PeakUsage_noMP_GeneLocAnno/
    Untracked:  data/PeaksUsed/
    Untracked:  data/PeaksUsed_noMP_5percCov/
    Untracked:  data/PolyA_DB/
    Untracked:  data/QTL_overlap/
    Untracked:  data/RNAdecay/
    Untracked:  data/RNAkalisto/
    Untracked:  data/RefSeq_annotations/
    Untracked:  data/Replicates_usage/
    Untracked:  data/Signal_Loc/
    Untracked:  data/TNcompExamp/
    Untracked:  data/TotalApaQTLs.txt
    Untracked:  data/Totalpeaks_filtered_clean.bed
    Untracked:  data/UnderstandPeaksQC/
    Untracked:  data/WASP_STAT/
    Untracked:  data/YL-SP-18486-T-combined-genecov.txt
    Untracked:  data/YL-SP-18486-T_S9_R1_001-genecov.txt
    Untracked:  data/YL_QTL_test/
    Untracked:  data/apaExamp/
    Untracked:  data/apaExamp_proc/
    Untracked:  data/apaQTL_examp_noMP/
    Untracked:  data/bedgraph_peaks/
    Untracked:  data/bin200.5.T.nuccov.bed
    Untracked:  data/bin200.Anuccov.bed
    Untracked:  data/bin200.nuccov.bed
    Untracked:  data/clean_peaks/
    Untracked:  data/comb_map_stats.csv
    Untracked:  data/comb_map_stats.xlsx
    Untracked:  data/comb_map_stats_39ind.csv
    Untracked:  data/combined_reads_mapped_three_prime_seq.csv
    Untracked:  data/diff_iso_GeneLocAnno/
    Untracked:  data/diff_iso_proc/
    Untracked:  data/diff_iso_trans/
    Untracked:  data/eQTL_inAPA/
    Untracked:  data/eQTLs_Lietal/
    Untracked:  data/ensemble_to_genename.txt
    Untracked:  data/example_gene_peakQuant/
    Untracked:  data/explainProtVar/
    Untracked:  data/filtPeakOppstrand_cov_noMP_GeneLocAnno_5perc/
    Untracked:  data/filtered_APApeaks_merged_allchrom_refseqTrans.closest2End.bed
    Untracked:  data/filtered_APApeaks_merged_allchrom_refseqTrans.closest2End.noties.bed
    Untracked:  data/first50lines_closest.txt
    Untracked:  data/gencov.test.csv
    Untracked:  data/gencov.test.txt
    Untracked:  data/gencov_zero.test.csv
    Untracked:  data/gencov_zero.test.txt
    Untracked:  data/gene_cov/
    Untracked:  data/joined
    Untracked:  data/leafcutter/
    Untracked:  data/merged_combined_YL-SP-threeprimeseq.bg
    Untracked:  data/molPheno_noMP/
    Untracked:  data/mol_overlap/
    Untracked:  data/mol_pheno/
    Untracked:  data/nom_QTL/
    Untracked:  data/nom_QTL_opp/
    Untracked:  data/nom_QTL_trans/
    Untracked:  data/nuc6up/
    Untracked:  data/nuc_10up/
    Untracked:  data/other_qtls/
    Untracked:  data/pQTL_inAPA/
    Untracked:  data/pQTL_otherphen/
    Untracked:  data/pacbio_cov/
    Untracked:  data/peakPerRefSeqGene/
    Untracked:  data/peaks4DT/
    Untracked:  data/perm_QTL/
    Untracked:  data/perm_QTL_GeneLocAnno_noMP_5percov/
    Untracked:  data/perm_QTL_GeneLocAnno_noMP_5percov_3UTR/
    Untracked:  data/perm_QTL_diffWindow/
    Untracked:  data/perm_QTL_opp/
    Untracked:  data/perm_QTL_trans/
    Untracked:  data/perm_QTL_trans_filt/
    Untracked:  data/protAndAPAAndExplmRes.Rda
    Untracked:  data/protAndAPAlmRes.Rda
    Untracked:  data/protAndExpressionlmRes.Rda
    Untracked:  data/reads_mapped_three_prime_seq.csv
    Untracked:  data/smash.cov.results.bed
    Untracked:  data/smash.cov.results.csv
    Untracked:  data/smash.cov.results.txt
    Untracked:  data/smash_testregion/
    Untracked:  data/ssFC200.cov.bed
    Untracked:  data/temp.file1
    Untracked:  data/temp.file2
    Untracked:  data/temp.gencov.test.txt
    Untracked:  data/temp.gencov_zero.test.txt
    Untracked:  data/threePrimeSeqMetaData.csv
    Untracked:  data/threePrimeSeqMetaData55Ind.txt
    Untracked:  data/threePrimeSeqMetaData55Ind.xlsx
    Untracked:  data/threePrimeSeqMetaData55Ind_noDup.txt
    Untracked:  data/threePrimeSeqMetaData55Ind_noDup.xlsx
    Untracked:  data/threePrimeSeqMetaData55Ind_noDup_WASPMAP.txt
    Untracked:  data/threePrimeSeqMetaData55Ind_noDup_WASPMAP.xlsx
    Untracked:  data/threePrimeSeqMetaData55Ind_redobatch4.xlsx
    Untracked:  data/~$threePrimeSeqMetaData55Ind_redobatch4.xlsx
    Untracked:  manuscript/
    Untracked:  output/APAqtlExamp/
    Untracked:  output/LZ/
    Untracked:  output/deeptools_plots/
    Untracked:  output/picard/
    Untracked:  output/plots/
    Untracked:  output/qual.fig2.pdf

Unstaged changes:
    Modified:   analysis/28ind.peak.explore.Rmd
    Modified:   analysis/CompareLianoglouData.Rmd
    Modified:   analysis/HistoneModandPAS.Rmd
    Modified:   analysis/NewPeakPostMP.Rmd
    Modified:   analysis/NuclearSpecQTL.Rmd
    Modified:   analysis/PeakToXper.Rmd
    Modified:   analysis/RNAdecayAndAPA.Rmd
    Modified:   analysis/apaQTLoverlapGWAS.Rmd
    Modified:   analysis/characterize_apaQTLs.Rmd
    Modified:   analysis/cleanupdtseq.internalpriming.Rmd
    Modified:   analysis/coloc_apaQTLs_protQTLs.Rmd
    Modified:   analysis/dif.iso.usage.leafcutter.Rmd
    Modified:   analysis/diffIsoAnalysisNewMapping.Rmd
    Modified:   analysis/diff_iso_pipeline.Rmd
    Modified:   analysis/explainpQTLs.Rmd
    Modified:   analysis/explore.filters.Rmd
    Modified:   analysis/fixBWChromNames.Rmd
    Modified:   analysis/flash2mash.Rmd
    Modified:   analysis/initialPacBioQuant.Rmd
    Modified:   analysis/mispriming_approach.Rmd
    Modified:   analysis/overlapMolQTL.Rmd
    Modified:   analysis/overlapMolQTL.opposite.Rmd
    Modified:   analysis/overlap_qtls.Rmd
    Modified:   analysis/peakOverlap_oppstrand.Rmd
    Modified:   analysis/peakQCPPlots.Rmd
    Modified:   analysis/pheno.leaf.comb.Rmd
    Modified:   analysis/pipeline_55Ind.Rmd
    Modified:   analysis/swarmPlots_QTLs.Rmd
    Modified:   analysis/test.max2.Rmd
    Modified:   analysis/test.smash.Rmd
    Modified:   analysis/understandPeaks.Rmd
    Modified:   analysis/unexplainedeQTL_analysis.Rmd
    Modified:   code/Snakefile

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 a79791b Briana Mittleman 2019-04-03 start tot nuc example plots 
library(tidyverse)
── Attaching packages ──────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.1.0       ✔ purrr   0.3.1  
✔ tibble  2.0.1       ✔ dplyr   0.8.0.1
✔ tidyr   0.8.3       ✔ stringr 1.4.0  
✔ readr   1.3.1       ✔ forcats 0.4.0  
Warning: package 'tibble' was built under R version 3.5.2
Warning: package 'tidyr' was built under R version 3.5.2
Warning: package 'purrr' was built under R version 3.5.2
Warning: package 'dplyr' was built under R version 3.5.2
Warning: package 'stringr' was built under R version 3.5.2
Warning: package 'forcats' was built under R version 3.5.2
── Conflicts ─────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
library(reshape2)

Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':

    smiths

Heatmap in one gene

I want to make an example heatmap for the total vs nuclear difference similar to the ones I did for the qtls.

I will take a similar approach where I make one then create a script to make it for all examples

chr21:43762910:43762982:TFF2

Count data is in:

/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_GeneLocAnno_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.GeneLocAnno_sm_quant_processed_fixed.fc

grep TFF2 /project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_GeneLocAnno_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.GeneLocAnno_sm_quant_processed_fixed.fc > /project2/gilad/briana/threeprimeseq/data/TNcompExamp/TNcomp_TFF2.txt

I will need to divide by the mapped read counts for the library:

metadata=read.table("../data/threePrimeSeqMetaData55Ind_noDup_WASPMAP.txt",header = T) %>% select(Sample_ID,Mapped_noMP )

metadata_melt=melt(metadata, id.vars = c("Sample_ID"), value.name = "MappedRead") %>% mutate(MappPM=MappedRead/10^6)

Header file:

TNhead=read.table("../data/TNcompExamp/TNCountheader.txt", header = T,stringsAsFactors = F)

read in data and melt it:

TN_TFF2=read.table("../data/TNcompExamp/TNcomp_TFF2.txt", col.names =colnames(TNhead),stringsAsFactors = F) %>% select(-Chr,-Geneid,-Strand, -Length)

TN_TFF2$Start=as.character(TN_TFF2$Start)
TN_TFF2$End=as.character(TN_TFF2$End)

TN_TFF2= TN_TFF2 %>% mutate(PeakLoc= paste(Start,End,sep="_")) %>% select(-Start, -End)

TN_TFF2_melt=melt(TN_TFF2, id.vars =c("PeakLoc"), variable.name = "ID", value.name = "PeakCount" ) %>% mutate(Sample_ID=substr(ID, 2, length(ID)))

Join:

TN_TFF2_withMeta=TN_TFF2_melt %>% inner_join(metadata_melt, by=c("Sample_ID")) %>% mutate(Fraction=ifelse(grepl("T",Sample_ID), "Total","Nuclear")) %>%  mutate(NormCount=PeakCount/MappPM) %>% group_by(PeakLoc,Fraction) %>% summarise(meanCPM=mean(NormCount))
Warning: Column `Sample_ID` joining character vector and factor, coercing
into character vector
my_palette <- colorRampPalette(c("white", "khaki1", "orange", "red", "darkred", "black"))

ggplot(TN_TFF2_withMeta, aes(x=PeakLoc, y=Fraction)) + geom_tile(aes(fill = meanCPM))+ scale_fill_gradientn(colors =my_palette(100)) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) + labs(x="PAS", title="TFF2")

Super low expression of this gene. Better example when it is

Generalize:



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     

other attached packages:
 [1] reshape2_1.4.3  forcats_0.4.0   stringr_1.4.0   dplyr_0.8.0.1  
 [5] purrr_0.3.1     readr_1.3.1     tidyr_0.8.3     tibble_2.0.1   
 [9] ggplot2_3.1.0   tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0       cellranger_1.1.0 plyr_1.8.4       pillar_1.3.1    
 [5] compiler_3.5.1   git2r_0.24.0     workflowr_1.2.0  tools_3.5.1     
 [9] digest_0.6.18    lubridate_1.7.4  jsonlite_1.6     evaluate_0.13   
[13] nlme_3.1-137     gtable_0.2.0     lattice_0.20-38  pkgconfig_2.0.2 
[17] rlang_0.3.1      cli_1.0.1        rstudioapi_0.9.0 yaml_2.2.0      
[21] haven_2.1.0      xfun_0.5         withr_2.1.2      xml2_1.2.0      
[25] httr_1.4.0       knitr_1.21       hms_0.4.2        generics_0.0.2  
[29] fs_1.2.6         rprojroot_1.3-2  grid_3.5.1       tidyselect_0.2.5
[33] glue_1.3.0       R6_2.4.0         readxl_1.3.0     rmarkdown_1.11  
[37] modelr_0.1.4     magrittr_1.5     whisker_0.3-2    backports_1.1.3 
[41] scales_1.0.0     htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0
[45] colorspace_1.4-0 labeling_0.3     stringi_1.3.1    lazyeval_0.2.1  
[49] munsell_0.5.0    broom_0.5.1      crayon_1.3.4