Last updated: 2019-02-07
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(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.
✔ Repository version: 3fea644
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/DirectionapaQTL.Rmd
Untracked: analysis/EvaleQTLs.Rmd
Untracked: analysis/YL_QTL_test.Rmd
Untracked: analysis/ncbiRefSeq_sm.sort.mRNA.bed
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/ApaQTLs/
Untracked: data/ChromHmmOverlap/
Untracked: data/DistTXN2Peak_genelocAnno/
Untracked: data/GM12878.chromHMM.bed
Untracked: data/GM12878.chromHMM.txt
Untracked: data/LianoglouLCL/
Untracked: data/LocusZoom/
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/RNAkalisto/
Untracked: data/RefSeq_annotations/
Untracked: data/TotalApaQTLs.txt
Untracked: data/Totalpeaks_filtered_clean.bed
Untracked: data/UnderstandPeaksQC/
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/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/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_otherphen/
Untracked: data/peakPerRefSeqGene/
Untracked: data/perm_QTL/
Untracked: data/perm_QTL_GeneLocAnno_noMP_5percov/
Untracked: data/perm_QTL_GeneLocAnno_noMP_5percov_3UTR/
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: output/picard/
Untracked: output/plots/
Untracked: output/qual.fig2.pdf
Unstaged changes:
Modified: analysis/28ind.peak.explore.Rmd
Modified: analysis/CompareLianoglouData.Rmd
Modified: analysis/apaQTLoverlapGWAS.Rmd
Modified: analysis/cleanupdtseq.internalpriming.Rmd
Modified: analysis/coloc_apaQTLs_protQTLs.Rmd
Modified: analysis/dif.iso.usage.leafcutter.Rmd
Modified: analysis/diff_iso_pipeline.Rmd
Modified: analysis/explainpQTLs.Rmd
Modified: analysis/explore.filters.Rmd
Modified: analysis/flash2mash.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/understandPeaks.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.
File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 3fea644 | Briana Mittleman | 2019-02-07 | add accountmapbias |
We are worried there amy be false positives in the QTL analysis if the QTL is in the read and the snp leads to a mapping bias for the data. I can account for this using WASP.
I have an example script from Yang:
/project2/yangili1/yangili/TCGA_pipe/script_process.sh
STAR2.6 --genomeDir /project2/yangili1/RNAseq_pipeline/index/GRCh37/STAR_hg19 --readFilesIn $inFile\_1.fastq $inFile\_2.fastq --outSAMstrandField intronMotif --outFileNamePrefix $outFile. --outSAMtype BAM Unsorted --varVCFfile $vcfFile --waspOutputMode SAMtag --outSAMattributes vA vG
First I need to find my star indexed genome:
*/project2/gilad/briana/genome_anotation_data/star_genome
Next I need my VCF file:
runStarwWASP.sh
#!/bin/bash
#SBATCH --job-name=runStarwWASP
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=runStarwWASP.out
#SBATCH --error=runStarwWASP.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
in=$1
out=$2
STAR --runThreadN 4 --genomeDir /project2/gilad/briana/genome_anotation_data/star_genome --readFilesIn $1 --outSAMstrandField intronMotif --outFileNamePrefix /project2/gilad/briana/threeprimeseq/data/STAR_bam_WASP/$2.combined.STARwWASP.bam --outSAMtype BAM Unsorted --varVCFfile /project2/gilad/briana/YRI_geno_hg19/allChrom.dose.filt.vcf --waspOutputMode SAMtag --outSAMattributes vA vG
test_runStartwWASP.sh
#!/bin/bash
#SBATCH --job-name=test_runStarwWASP
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=test_runStarwWASP.out
#SBATCH --error=test_runStarwWASP.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
i=/project2/gilad/briana/threeprimeseq/data/fastq/YL-SP-19239-T-combined.fastq
describer=$(echo ${i} | sed -e 's/.*YL-SP-//' | sed -e "s/combined.fastq//")
sbatch runStarwWASP.sh $i $describer
Wraper:
wrap_runStarwWASP.sh
#!/bin/bash
#SBATCH --job-name=wrap_runStarwWASP
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=wrap_runStarwWASP.out
#SBATCH --error=wrap_runStarwWASP.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
for i in $(ls /project2/gilad/briana/threeprimeseq/data/fastq/*);do
describer=$(echo ${i} | sed -e 's/.*YL-SP-//' | sed -e "s/combined.fastq//")
sbatch runStarwWASP.sh $i $describer
done
Quota reached at 19193N for jobs- create a wrap2
wrap_runStarwWASP2.sh
#!/bin/bash
#SBATCH --job-name=wrap_runStarwWASP2
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=wrap_runStarwWASP2.out
#SBATCH --error=wrap_runStarwWASP2.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
for i in $(ls /project2/gilad/briana/threeprimeseq/data/fastq/YL-SP-192*); do
describer=$(echo ${i} | sed -e 's/.*YL-SP-//' | sed -e "s/combined.fastq//")
sbatch runStarwWASP.sh $i $describer
done
Sort and index these files.
SortIndexStarwWASP.sh
#!/bin/bash
#SBATCH --job-name=SortIndexStarwWASP
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=SortIndexStarwWASP.out
#SBATCH --error=SortIndexStarwWASP.err
#SBATCH --partition=broadwl
#SBATCH --mem=36G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
describer=$1
samtools sort /project2/gilad/briana/threeprimeseq/data/STAR_bam_WASP/${describer}combined.STARwWASP.bamAligned.out.bam > /project2/gilad/briana/threeprimeseq/data/STAR_bam_WASP_sort/${describer}combined.STARwWASP.bamAligned.sort.bam
samtools index /project2/gilad/briana/threeprimeseq/data/STAR_bam_WASP_sort/${describer}combined.STARwWASP.bamAligned.sort.bam
wrap_SortIndexStarwWASP.sh
#!/bin/bash
#SBATCH --job-name=wrap_SortIndexStarwWASP
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=wrap_SortIndexStarwWASP.out
#SBATCH --error=wrap_SortIndexStarwWASP.err
#SBATCH --partition=broadwl
#SBATCH --mem=36G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
for i in $(ls /project2/gilad/briana/threeprimeseq/data/STAR_bam_WASP/*STARwWASP.bamAligned.out.bam)
describer=$(echo ${i} | sed -e 's/.*YL-SP-//' | sed -e "s/combined.STARwWASP.bamAligned.out.bam//")
sbatch SortIndexStarwWASP.sh $describer
done
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_1.1.1 Rcpp_0.12.19 digest_0.6.17
[4] rprojroot_1.3-2 R.methodsS3_1.7.1 backports_1.1.2
[7] git2r_0.23.0 magrittr_1.5 evaluate_0.11
[10] stringi_1.2.4 whisker_0.3-2 R.oo_1.22.0
[13] R.utils_2.7.0 rmarkdown_1.10 tools_3.5.1
[16] stringr_1.3.1 yaml_2.2.0 compiler_3.5.1
[19] htmltools_0.3.6 knitr_1.20
This reproducible R Markdown analysis was created with workflowr 1.1.1