Last updated: 2019-03-13
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Knit directory: threeprimeseq/analysis/
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Unstaged changes:
Modified: analysis/28ind.peak.explore.Rmd
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Modified: analysis/unexplainedeQTL_analysis.Rmd
Modified: code/Snakefile
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File | Version | Author | Date | Message |
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html | 416ce21 | Briana Mittleman | 2019-02-28 | Build site. |
Rmd | ea34b3c | Briana Mittleman | 2019-02-28 | add nuclear spec peaks |
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(workflowr)
This is workflowr version 1.2.0
Run ?workflowr for help getting started
merge net seq data:
/project2/gilad/briana/Net-seq/Net-seq3/data/sort/*-sort.bam
/project2/gilad/briana/Net-seq/Net-seq3/data/sort/mergeAndMakeBWnet3.sh
#!/bin/bash
#SBATCH --job-name=mergeAndMakeBWnet3
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=mergeAndMakeBWnet3.out
#SBATCH --error=mergeAndMakeBWnet3.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
samtools merge /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.bam /project2/gilad/briana/Net-seq/Net-seq3/data/sort/*-sort.bam
samtools sort /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.bam > /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bam
samtools index /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bam
bamCoverage -b /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bam -o /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw
Look 3kb on each side
NetseqDTPlotmyPeaks_noMPFilt.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlotmyPeaks_noMPFilt
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlotmyPeaks_noMPFilt.out
#SBATCH --error=NetseqDTPlotmyPeaks_noMPFilt.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myPeaksNompfilt.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myPeaksNompfilt.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at All Called PAS" --heatmapHeight 7 --colorMap YlGnBu -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myPeaksNompfilt.png
Do this for intronic peaks
NetseqDTPlotmyIntronPeaks_noMPFilt.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlotmyIntronPeaks_noMPFilt
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlotmyIntronPeaks_noMPFilt.out
#SBATCH --error=NetseqDTPlotmyIntronPeaks_noMPFilt.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_INTRON.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myIntronPeaksNompfilt.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myIntronPeaksNompfilt.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Intronic Called PAS" --heatmapHeight 7 --colorMap YlGnBu -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myIntronPeaksNompfilt.png
Top used intronic in nuclear
NetseqDTPlotmyToptIntronPeaks_noMPFilt.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlotmyToptIntronPeaks_noMPFilt
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlotmyTopIntronPeaks_noMPFilt.out
#SBATCH --error=NetseqDTPlotmyTopIntronPeaks_noMPFilt.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_INTRON_top200Usage.Nuclear.sort.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myTopIntronPeaksNompfilt.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myTopIntronPeaksNompfilt.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Top Nuclear Intronic Called PAS" --heatmapHeight 7 --colorMap YlGnBu -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myTotIntronPeaksNompfilt.png
/project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_INTRON_top200Usage_Total.sort.bed NetseqDTPlotmyTopTotIntronPeaks_noMPFilt.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlotmyTopTotIntronPeaks_noMPFilt
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlotmyTopTotIntronPeaks_noMPFilt.out
#SBATCH --error=NetseqDTPlotmyTopTotIntronTotPeaks_noMPFilt.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_INTRON_top200Usage_Total.sort.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myTopTotIntronPeaksNompfilt.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myTopTotIntronPeaksNompfilt.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Top Total Intronic Called PAS" --heatmapHeight 7 --colorMap YlGnBu -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myTopTotIntronPeaksNompfilt.png
UTR peaks
NetseqDTPlotmyUTRPeaks_noMPFilt.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlotmyUTRPeaks_noMPFilt
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlotmyUTRPeaks_noMPFilt.out
#SBATCH --error=NetseqDTPlotmyUTRPeaks_noMPFilt.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/mergedPeaks_noMP_GeneLoc_3UTR/Filtered_APApeaks_merged_allchrom_noMP.sort.named.noCHR_geneLocParsed_5perc_FixedStrand_3UTR.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myUTRPeaksNompfilt.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myUTRPeaksNompfilt.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at 3' UTR Called PAS" --heatmapHeight 7 --colorMap YlGnBu -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_myUTRPeaksNompfilt.png
I want to look at the peaks used more often in the nucelear fraction and see if we have enrichment at these.
NucPeaks=read.table("../data/diff_iso_GeneLocAnno/SigPeaksHigherInNuc.txt", header=T, stringsAsFactors = F) %>% separate(intron, into=c("Chr2", "Start", "End", "gene"), sep=":")
NucPeaks$Start=as.numeric(NucPeaks$Start)
NucPeaks$End=as.numeric(NucPeaks$End)
Now I want to pull in the corrected strand peaks.
DTPeaks=read.table("../data/peaks4DT/APAPeaks_5percCov_fixedStrand.bed",header = F, col.names = c("Chr", "Start", "End","Name", "Score", "Strand" )) %>% mutate(Chr2=paste("chr", Chr, sep=""))
DTPeaks_filt=DTPeaks %>% semi_join(NucPeaks, by=c("Chr2", "Start", "End")) %>% select(-Chr2)
#write it
write.table(DTPeaks_filt, "../data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc.bed", col.names = F, row.names = F, quote=F, sep="\t")
NetseqDTPlot_NucDiffUsedPeaks_noMPFilt.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlot_NucDiffUsedPeaks_noMPFilt
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlot_NucDiffUsedPeaks_noMPFilt.out
#SBATCH --error=NetseqDTPlot_NucDiffUsedPeaks_noMPFilt.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Nuclear Specific PAS" --heatmapHeight 7 --colorMap YlGnBu --averageTypeSummaryPlot "mean" -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt.png
There are a few peaks driving the signal. I can split these up into 5 peak files
DTPeaks_filt_1= DTPeaks_filt %>% slice(1:150)
DTPeaks_filt_2= DTPeaks_filt %>% slice(151:300)
DTPeaks_filt_3= DTPeaks_filt %>% slice(301:450)
DTPeaks_filt_4= DTPeaks_filt %>% slice(451:600)
DTPeaks_filt_5= DTPeaks_filt %>% slice(601:762)
write.table(DTPeaks_filt_1, "../data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_1.bed", col.names = F, row.names = F, quote=F, sep="\t")
write.table(DTPeaks_filt_2, "../data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_2.bed", col.names = F, row.names = F, quote=F, sep="\t")
write.table(DTPeaks_filt_3, "../data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_3.bed", col.names = F, row.names = F, quote=F, sep="\t")
write.table(DTPeaks_filt_4, "../data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_4.bed", col.names = F, row.names = F, quote=F, sep="\t")
write.table(DTPeaks_filt_5, "../data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_5.bed", col.names = F, row.names = F, quote=F, sep="\t")
NetseqDTPlot_NucDiffUsedPeaks_noMPFilt_5plots.sh
#!/bin/bash
#SBATCH --job-name=NetseqDTPlot_NucDiffUsedPeaks_noMPFilt_5plots
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=NetseqDTPlot_NucDiffUsedPeaks_noMPFilt_5plots.out
#SBATCH --error=NetseqDTPlot_NucDiffUsedPeaks_noMPFilt_5plots.err
#SBATCH --partition=bigmem2
#SBATCH --mem=100G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
#1
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_1.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt1.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt1.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Nuclear Specific PAS" --heatmapHeight 7 --colorMap YlGnBu --averageTypeSummaryPlot "mean" -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt1.png
#2
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_2.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt2.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt2.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Nuclear Specific PAS" --heatmapHeight 7 --colorMap YlGnBu --averageTypeSummaryPlot "mean" -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt2.png
#3
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_3.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt3.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt3.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Nuclear Specific PAS" --heatmapHeight 7 --colorMap YlGnBu --averageTypeSummaryPlot "mean" -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt3.png
#4
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_4.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt4.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt4.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Nuclear Specific PAS" --heatmapHeight 7 --colorMap YlGnBu --averageTypeSummaryPlot "mean" -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt4.png
#5
computeMatrix reference-point -S /project2/gilad/briana/Net-seq/Net-seq3/data/sort/Merged.Net3.sort.bw -R /project2/gilad/briana/threeprimeseq/data/peaks4DT/APAPeaks_5percCov_fixedStrand_SigUsageNuc_5.bed -b 3000 -a 3000 -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt5.gz
plotHeatmap --sortRegions descend -m /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt5.gz --refPointLabel "Called PAS" --plotTitle "Combined NetSeq at Nuclear Specific PAS" --heatmapHeight 7 --colorMap YlGnBu --averageTypeSummaryPlot "mean" -out /project2/gilad/briana/threeprimeseq/data/LianoglouDeepTools/Netseq_NucDiffUsedPeaksNompfilt5.png
Data are a bit too noisy to say anything here.
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] workflowr_1.2.0 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 tools_3.5.1 digest_0.6.18
[9] lubridate_1.7.4 jsonlite_1.6 evaluate_0.13 nlme_3.1-137
[13] gtable_0.2.0 lattice_0.20-38 pkgconfig_2.0.2 rlang_0.3.1
[17] cli_1.0.1 rstudioapi_0.9.0 yaml_2.2.0 haven_2.1.0
[21] xfun_0.5 withr_2.1.2 xml2_1.2.0 httr_1.4.0
[25] knitr_1.21 hms_0.4.2 generics_0.0.2 fs_1.2.6
[29] rprojroot_1.3-2 grid_3.5.1 tidyselect_0.2.5 glue_1.3.0
[33] R6_2.4.0 readxl_1.3.0 rmarkdown_1.11 modelr_0.1.4
[37] magrittr_1.5 whisker_0.3-2 backports_1.1.3 scales_1.0.0
[41] htmltools_0.3.6 rvest_0.3.2 assertthat_0.2.0 colorspace_1.4-0
[45] stringi_1.3.1 lazyeval_0.2.1 munsell_0.5.0 broom_0.5.1
[49] crayon_1.3.4