Last updated: 2018-07-19
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 8398e0e | Briana Mittleman | 2018-07-19 | run on all ind |
html | 652b7e9 | Briana Mittleman | 2018-07-19 | Build site. |
Rmd | 31482e2 | Briana Mittleman | 2018-07-19 | gapdh |
html | 3193223 | Briana Mittleman | 2018-07-18 | Build site. |
Rmd | 9d32076 | Briana Mittleman | 2018-07-18 | add actb example |
html | 0464829 | Briana Mittleman | 2018-07-17 | Build site. |
Rmd | cc5cc50 | Briana Mittleman | 2018-07-17 | test region smash results |
html | d61f590 | Briana Mittleman | 2018-07-17 | Build site. |
Rmd | 89ebcac | Briana Mittleman | 2018-07-17 | add smash test |
In this analysis I will use the tutorial I did for the SMASH package on chip seq data to test it on the three prime seq data. In order to complete this I need to make a matrix with genome location counts for where reads start for positions 880001:1011072 on chr1, I am using this region because I already know it fits the \(2^{x}\) criterion. I need the matrix to be individual by basepair. I can use genome cov in all of the total fractions then merge the results together to make a matrix.
#!/bin/bash
#SBATCH --job-name=5gencov
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=5gencov.out
#SBATCH --error=5gencov.err
#SBATCH --partition=broadwl
#SBATCH --mem=40G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
#imput sorted bam file
bam=$1
describer=$(echo ${bam} | sed -e 's/.*\YL-SP-//' | sed -e "s/-sort.bam$//")
bedtools genomecov-ibam $1 -d -5 > /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.${describer}.bed
run on /project2/gilad/briana/threeprimeseq/data/sort/YL-SP-18486-N_S10_R1_001-sort.bam
wrap this function:
#!/bin/bash
#SBATCH --job-name=w_5gencov
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=w_5gencov.out
#SBATCH --error=w_5gencov.err
#SBATCH --partition=broadwl
#SBATCH --mem=16G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
for i in $(ls /project2/gilad/briana/threeprimeseq/data/sort/*.bam); do
sbatch 5primegencov.sh $i
done
First I will get ch1 880001:1011072 for each individual.
#!/bin/bash
#SBATCH --job-name=test.reg
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=test.reg.out
#SBATCH --error=test.reg.err
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18486-T_S9_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18486-T_S9_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18497-T_S11_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18497-T_S11_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 &5& $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18500-T_S19_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18500-T_S19_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18505-T_S1_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18505-T_S1_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' gencov5prime.18508-T_S5_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18508-T_S5_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}'/project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18853-T_S31_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18853-T_S31_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18870-T_S23_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18870-T_S23_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19128-T_S29_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19128-T_S29_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19141-T_S17_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19141-T_S17_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19193-T_S21_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19193-T_S21_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19209-T_S15_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19209-T_S15_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19233-T_S7_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19223-T_S7_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19225-T_S27_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19225-T_S27_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19238-T_S3_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19238-T_S3_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19239-T_S13_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19239-T_S13_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19257-T_S25_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19257-T_S25_R1_001.testregion.bed
3 didnt work. Try these again.
#!/bin/bash
#SBATCH --job-name=test.reg2
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=test.reg2.out
#SBATCH --error=test.reg2.err
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18508-T_S5_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18508-T_S5_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18853-T_S31_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18853-T_S31_R1_001.testregion.bed
awk '$1 == 1 && $2 >= 880001 && $2 <= 1011072 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18500-T_S19_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18500-T_S19_R1_001.testregion.bed
Now I will pull in these regions and merge them to make a matrix I can put into smashr.
test_18468=read.table("../data/smash_testregion/gencov5prime.18486-T_S9_R1_001.testregion.bed", col.names=c("chr", "base", "T18486"))
test_18497=read.table("../data/smash_testregion/gencov5prime.18497-T_S11_R1_001.testregion.bed", col.names=c("chr", "base", "T18497"))
test_18500=read.table("../data/smash_testregion/gencov5prime.18500-T_S19_R1_001.testregion.bed", col.names=c("chr", "base", "T18500"))
test_18505=read.table("../data/smash_testregion/gencov5prime.18505-T_S1_R1_001.testregion.bed", col.names=c("chr", "base", "T18505"))
test_18508=read.table("../data/smash_testregion/gencov5prime.18508-T_S5_R1_001.testregion.bed", col.names=c("chr", "base", "T18508"))
test_18853=read.table("../data/smash_testregion/gencov5prime.18853-T_S31_R1_001.testregion.bed", col.names=c("chr", "base", "T18853"))
test_18870=read.table("../data/smash_testregion/gencov5prime.18870-T_S23_R1_001.testregion.bed", col.names=c("chr", "base", "T18870"))
test_19128=read.table("../data/smash_testregion/gencov5prime.19128-T_S29_R1_001.testregion.bed", col.names=c("chr", "base", "T19128"))
test_19239=read.table("../data/smash_testregion/gencov5prime.19239-T_S13_R1_001.testregion.bed", col.names=c("chr", "base", "T19239"))
test_19257=read.table("../data/smash_testregion/gencov5prime.19257-T_S25_R1_001.testregion.bed", col.names=c("chr", "base", "T19257"))
test_19141=read.table("../data/smash_testregion/gencov5prime.19141-T_S17_R1_001.testregion.bed", col.names=c("chr", "base", "T19141"))
test_19193=read.table("../data/smash_testregion/gencov5prime.19193-T_S21_R1_001.testregion.bed", col.names=c("chr", "base", "T19193"))
test_19209=read.table("../data/smash_testregion/gencov5prime.19209-T_S15_R1_001.testregion.bed", col.names=c("chr", "base", "T19209"))
test_19223=read.table("../data/smash_testregion/gencov5prime.19223-T_S7_R1_001.testregion.bed", col.names=c("chr", "base", "T19223"))
test_19225=read.table("../data/smash_testregion/gencov5prime.19225-T_S27_R1_001.testregion.bed", col.names=c("chr", "base", "T19225"))
test_19238=read.table("../data/smash_testregion/gencov5prime.19238-T_S3_R1_001.testregion.bed", col.names=c("chr", "base", "T19238"))
Load Packages:
library(devtools)
Warning: package 'devtools' was built under R version 3.4.4
library(scales)
library(smashr)
library(tidyr)
library(workflowr)
Loading required package: rmarkdown
This is workflowr version 1.0.1
Run ?workflowr for help getting started
library(dplyr)
Warning: package 'dplyr' was built under R version 3.4.4
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Bind all of the count
test_matrix=cbind(test_18468$T18486, test_18497$T18497, test_18500$T18500, test_18505$T18505, test_18508$T18508, test_18853$T18853, test_18870$T18870, test_19128$T19128, test_19141$T19141, test_19193$T19193, test_19209$T19209, test_19223$T19223, test_19225$T19225, test_19238$T19238, test_19239$T19239, test_19257$T19257) %>% t
Run smash:
res = smash.poiss(test_matrix[1,]+test_matrix[2,],post.var=TRUE)
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 316440
Objective fn: 75069.3 Extrapolation: 0 Steplength: 1
Objective fn: 20919.7 Extrapolation: 1 Steplength: 1.7761
Objective fn: 17547 Extrapolation: 1 Steplength: 4
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Objective fn: 16836.6 Extrapolation: 1 Steplength: 1.86253
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Objective fn: 16816 Extrapolation: 1 Steplength: 1.66778
Objective fn: 16815.9 Extrapolation: 1 Steplength: 7.08232
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 547800
Objective fn: 101309 Extrapolation: 0 Steplength: 1
Objective fn: 37390.2 Extrapolation: 1 Steplength: 1.89191
Objective fn: 32343.6 Extrapolation: 1 Steplength: 4
Objective fn: 31416.8 Extrapolation: 1 Steplength: 5.23485
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Objective fn: 31003.4 Extrapolation: 1 Steplength: 2.25357
Objective fn: 31003.3 Extrapolation: 1 Steplength: 6.79538
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 882921
Objective fn: 118772 Extrapolation: 0 Steplength: 1
Objective fn: 49764.5 Extrapolation: 1 Steplength: 1.87244
Objective fn: 44341.9 Extrapolation: 1 Steplength: 4
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Objective fn: 41406.9 Extrapolation: 1 Steplength: 5.74521
Objective fn: 41406.8 Extrapolation: 1 Steplength: 3.48951
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 1.2791e+06
Objective fn: 88217.7 Extrapolation: 0 Steplength: 1
Objective fn: 48098 Extrapolation: 1 Steplength: 3.21173
Objective fn: 41534.8 Extrapolation: 1 Steplength: 3.31029
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Objective fn: 38844.1 Extrapolation: 1 Steplength: 1.53262
Objective fn: 38843.9 Extrapolation: 1 Steplength: 6.32374
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 1.19992e+06
Objective fn: 127113 Extrapolation: 0 Steplength: 1
Objective fn: 103768 Extrapolation: 1 Steplength: 2.87597
Objective fn: 100999 Extrapolation: 1 Steplength: 4
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Objective fn: 98160.7 Extrapolation: 1 Steplength: 16
Objective fn: 98161.6 Extrapolation: 1 Steplength: 25.5964
Objective fn: 98160.7 Extrapolation: 1 Steplength: 4.9659
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Objective fn: 98161.4 Extrapolation: 1 Steplength: 28.4418
Objective fn: 98160.6 Extrapolation: 1 Steplength: 4.88053
Objective fn: 98161.5 Extrapolation: 1 Steplength: 64
Objective fn: 98160.9 Extrapolation: 1 Steplength: 1.58458
Objective fn: 98160.6 Extrapolation: 1 Steplength: 5.74946
Objective fn: 98160.7 Extrapolation: 1 Steplength: 18.0007
Objective fn: 98160.6 Extrapolation: 1 Steplength: 1.31963
Objective fn: 98160.8 Extrapolation: 1 Steplength: 14.5938
Objective fn: 98160.6 Extrapolation: 1 Steplength: 5.87148
Objective fn: 98160.6 Extrapolation: 1 Steplength: 2.79445
Objective fn: 98160.6 Extrapolation: 1 Steplength: 10.536
Objective fn: 98160.6 Extrapolation: 1 Steplength: 1.26176
Objective fn: 98160.6 Extrapolation: 0 Steplength: 1
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Objective fn: 98160.6 Extrapolation: 1 Steplength: 64
Objective fn: 98160.7 Extrapolation: 1 Steplength: 11.4375
Objective fn: 98160.6 Extrapolation: 1 Steplength: 3.26847
Objective fn: 98160.6 Extrapolation: 1 Steplength: 4.39932
Objective fn: 98160.6 Extrapolation: 1 Steplength: 3.21355
Objective fn: 98160.6 Extrapolation: 1 Steplength: 7.1878
Objective fn: 98160.6 Extrapolation: 1 Steplength: 1.51531
Objective fn: 98160.5 Extrapolation: 1 Steplength: 256
Objective fn: 98160.5 Extrapolation: 1 Steplength: 1.39451
Objective fn: 98160.7 Extrapolation: 1 Steplength: 479.942
Objective fn: 98160.5 Extrapolation: 1 Steplength: 1.41467
Objective fn: 98160.6 Extrapolation: 1 Steplength: 14.2088
Objective fn: 98160.5 Extrapolation: 1 Steplength: 2.52095
Objective fn: 98160.5 Extrapolation: 1 Steplength: 9.92198
Objective fn: 98160.5 Extrapolation: 1 Steplength: 2.79295
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 687462
Objective fn: 233579 Extrapolation: 0 Steplength: 1
Objective fn: 163301 Extrapolation: 1 Steplength: 2.96537
Objective fn: 101350 Extrapolation: 0 Steplength: 1
Objective fn: 87205.9 Extrapolation: 1 Steplength: 3.31731
Objective fn: 83310 Extrapolation: 1 Steplength: 1.41235
Objective fn: 83078.4 Extrapolation: 1 Steplength: 4
Objective fn: 83067.1 Extrapolation: 1 Steplength: 2.82442
Objective fn: 83065.1 Extrapolation: 1 Steplength: 2.48778
Objective fn: 83064.6 Extrapolation: 1 Steplength: 2.94018
Objective fn: 83064.5 Extrapolation: 1 Steplength: 2.28751
Objective fn: 83064.5 Extrapolation: 1 Steplength: 3.24189
bppos = 880001:1011072
plot(bppos,test_matrix[1,]+test_matrix[2,],xlab="position",ylab="counts",pch=16,cex=0.5, col=alpha("black",0.04))
Version | Author | Date |
---|---|---|
0464829 | Briana Mittleman | 2018-07-17 |
plot(bppos,res$est,type='l',xlab="position",ylab="intensity")
Version | Author | Date |
---|---|---|
0464829 | Briana Mittleman | 2018-07-17 |
Create a coverage file with the results.
cov=cbind(test_18468$chr, test_18468$base + 1, test_18468$base, res$est)
I want to try this on a region with higher background for example where actb is. I can run a smaller region of \(2^{10}\) bases. chr7:5,566,662-5,567,686. The following script to extract the region is called test.actbregion.sh.
#!/bin/bash
#SBATCH --job-name=test.regactb
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=test.regact.out
#SBATCH --error=test.regact.err
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18486-T_S9_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18486-T_S9_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18497-T_S11_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18497-T_S11_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18500-T_S19_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18500-T_S19_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18505-T_S1_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18505-T_S1_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18508-T_S5_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18508-T_S5_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18853-T_S31_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18853-T_S31_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18870-T_S23_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18870-T_S23_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19128-T_S29_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19128-T_S29_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19141-T_S17_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19141-T_S17_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19193-T_S21_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19193-T_S21_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19209-T_S15_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19209-T_S15_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19233-T_S7_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19223-T_S7_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19225-T_S27_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19225-T_S27_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19238-T_S3_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19238-T_S3_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19239-T_S13_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19239-T_S13_R1_001.testregion.actb.bed
awk '$1 == 7 && $2 >= 5566662 && $2 <= 5567686 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19257-T_S25_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19257-T_S25_R1_001.testregion.actb.bed
18853 did not work, running seperatly.
actb_test_18468=read.table("../data/smash_testregion/gencov5prime.18486-T_S9_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18486"))
actb_test_18497=read.table("../data/smash_testregion/gencov5prime.18497-T_S11_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18497"))
actb_test_18500=read.table("../data/smash_testregion/gencov5prime.18500-T_S19_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18500"))
actb_test_18505=read.table("../data/smash_testregion/gencov5prime.18505-T_S1_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18505"))
actb_test_18508=read.table("../data/smash_testregion/gencov5prime.18508-T_S5_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18508"))
actb_test_18853=read.table("../data/smash_testregion/gencov5prime.18853-T_S31_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18853"))
actb_test_18870=read.table("../data/smash_testregion/gencov5prime.18870-T_S23_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T18870"))
actb_test_19128=read.table("../data/smash_testregion/gencov5prime.19128-T_S29_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19128"))
actb_test_19239=read.table("../data/smash_testregion/gencov5prime.19239-T_S13_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19239"))
actb_test_19257=read.table("../data/smash_testregion/gencov5prime.19257-T_S25_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19257"))
actb_test_19141=read.table("../data/smash_testregion/gencov5prime.19141-T_S17_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19141"))
actb_test_19193=read.table("../data/smash_testregion/gencov5prime.19193-T_S21_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19193"))
actb_test_19209=read.table("../data/smash_testregion/gencov5prime.19209-T_S15_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19209"))
actb_test_19223=read.table("../data/smash_testregion/gencov5prime.19223-T_S7_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19223"))
actb_test_19225=read.table("../data/smash_testregion/gencov5prime.19225-T_S27_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19225"))
actb_test_19238=read.table("../data/smash_testregion/gencov5prime.19238-T_S3_R1_001.testregion.actb.bed", col.names=c("chr", "base", "T19238"))
Make matrix
actb_test_matrix=cbind(actb_test_18468$T18486, actb_test_18497$T18497, actb_test_18500$T18500, actb_test_18505$T18505, actb_test_18508$T18508, actb_test_18853$T18853, actb_test_18870$T18870, actb_test_19128$T19128, actb_test_19141$T19141, actb_test_19193$T19193, actb_test_19209$T19209, actb_test_19223$T19223, actb_test_19225$T19225, actb_test_19238$T19238, actb_test_19239$T19239, actb_test_19257$T19257) %>% t
Run smash:
actb_res = smash.poiss(actb_test_matrix[1,]+actb_test_matrix[2,]+ actb_test_matrix[3,]+actb_test_matrix[4,]+actb_test_matrix[5,]+actb_test_matrix[6,]+actb_test_matrix[7,]+actb_test_matrix[8,]+actb_test_matrix[9,]+actb_test_matrix[10,]+actb_test_matrix[11,]+actb_test_matrix[12,]+actb_test_matrix[13,]+actb_test_matrix[14,]+actb_test_matrix[15,]+actb_test_matrix[16,],post.var=TRUE)
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Make plots:
actb_bppos = 5566662:5567686
plot(actb_bppos,actb_test_matrix[1,]+actb_test_matrix[2,]+ actb_test_matrix[3,]+actb_test_matrix[4,]+actb_test_matrix[5,]+actb_test_matrix[6,]+actb_test_matrix[7,]+actb_test_matrix[8,]+actb_test_matrix[9,]+actb_test_matrix[10,]+actb_test_matrix[11,]+actb_test_matrix[12,]+actb_test_matrix[13,]+actb_test_matrix[14,]+actb_test_matrix[15,]+actb_test_matrix[16,],xlab="position",ylab="counts",pch=16,cex=0.5, col=alpha("black",.5), main="Raw data ACTB")
Version | Author | Date |
---|---|---|
652b7e9 | Briana Mittleman | 2018-07-19 |
3193223 | Briana Mittleman | 2018-07-18 |
plot(actb_bppos,actb_res$est,type='l',xlab="position",ylab="intensity", main="SMASH results ACTB")
Check on another highly expressed gene to see if this dual peak pattern appears again. I will look at GAPDH. Chr12 6,646,755-6,647,779
#!/bin/bash
#SBATCH --job-name=test.reggap
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=test.reggap.out
#SBATCH --error=test.reggap.err
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18486-T_S9_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18486-T_S9_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18497-T_S11_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18497-T_S11_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18500-T_S19_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18500-T_S19_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18505-T_S1_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18505-T_S1_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18508-T_S5_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18508-T_S5_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18853-T_S31_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18853-T_S31_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.18870-T_S23_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.18870-T_S23_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19128-T_S29_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19128-T_S29_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19141-T_S17_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19141-T_S17_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19193-T_S21_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19193-T_S21_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19209-T_S15_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19209-T_S15_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19233-T_S7_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19223-T_S7_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19225-T_S27_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19225-T_S27_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19238-T_S3_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19238-T_S3_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19239-T_S13_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19239-T_S13_R1_001.testregion.gap.bed
awk '$1 == 12 && $2 >= 6646755 && $2 <= 6647779 {print}' /project2/gilad/briana/threeprimeseq/data/test.smash/gencov5prime.19257-T_S25_R1_001.bed > /project2/gilad/briana/threeprimeseq/data/test.region/gencov5prime.19257-T_S25_R1_001.testregion.gap.bed
Pull in the data:
gap_test_18468=read.table("../data/smash_testregion/gencov5prime.18486-T_S9_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18486"))
gap_test_18497=read.table("../data/smash_testregion/gencov5prime.18497-T_S11_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18497"))
gap_test_18500=read.table("../data/smash_testregion/gencov5prime.18500-T_S19_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18500"))
gap_test_18505=read.table("../data/smash_testregion/gencov5prime.18505-T_S1_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18505"))
gap_test_18508=read.table("../data/smash_testregion/gencov5prime.18508-T_S5_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18508"))
gap_test_18853=read.table("../data/smash_testregion/gencov5prime.18853-T_S31_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18853"))
gap_test_18870=read.table("../data/smash_testregion/gencov5prime.18870-T_S23_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T18870"))
gap_test_19128=read.table("../data/smash_testregion/gencov5prime.19128-T_S29_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19128"))
gap_test_19239=read.table("../data/smash_testregion/gencov5prime.19239-T_S13_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19239"))
gap_test_19257=read.table("../data/smash_testregion/gencov5prime.19257-T_S25_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19257"))
gap_test_19141=read.table("../data/smash_testregion/gencov5prime.19141-T_S17_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19141"))
gap_test_19193=read.table("../data/smash_testregion/gencov5prime.19193-T_S21_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19193"))
gap_test_19209=read.table("../data/smash_testregion/gencov5prime.19209-T_S15_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19209"))
gap_test_19223=read.table("../data/smash_testregion/gencov5prime.19223-T_S7_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19223"))
gap_test_19225=read.table("../data/smash_testregion/gencov5prime.19225-T_S27_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19225"))
gap_test_19238=read.table("../data/smash_testregion/gencov5prime.19238-T_S3_R1_001.testregion.gap.bed", col.names=c("chr", "base", "T19238"))
Make matrix
gap_test_matrix=cbind(gap_test_18468$T18486, gap_test_18497$T18497, gap_test_18500$T18500, gap_test_18505$T18505, gap_test_18508$T18508, gap_test_18853$T18853, gap_test_18870$T18870, gap_test_19128$T19128, gap_test_19141$T19141, gap_test_19193$T19193, gap_test_19209$T19209, gap_test_19223$T19223, gap_test_19225$T19225, gap_test_19238$T19238, gap_test_19239$T19239, gap_test_19257$T19257) %>% t
Run smash:
gap_res = smash.poiss(gap_test_matrix[1,]+gap_test_matrix[2,]+gap_test_matrix[3,]+gap_test_matrix[4,]+gap_test_matrix[5,]+gap_test_matrix[6,]+gap_test_matrix[7,]+gap_test_matrix[8,]+gap_test_matrix[9,]+gap_test_matrix[10,]+gap_test_matrix[11,]+gap_test_matrix[12,]+gap_test_matrix[13,]+gap_test_matrix[14,]+gap_test_matrix[15,]+gap_test_matrix[15,]+ gap_test_matrix[16,],post.var=TRUE)
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Due to absence of package REBayes, switching to EM algorithm
Make plots:
gap_bppos =6646755:6647779
plot(gap_test_matrix[1,]+gap_test_matrix[2,]+gap_test_matrix[3,]+gap_test_matrix[4,]+gap_test_matrix[5,]+gap_test_matrix[6,]+gap_test_matrix[7,]+gap_test_matrix[8,]+gap_test_matrix[9,]+gap_test_matrix[10,]+gap_test_matrix[11,]+gap_test_matrix[12,]+gap_test_matrix[13,]+gap_test_matrix[14,]+gap_test_matrix[15,]+gap_test_matrix[15,]+ gap_test_matrix[16,],xlab="position",ylab="counts",pch=16,cex=0.5, col=alpha("black",.5), main="Raw data GAPDH")
Version | Author | Date |
---|---|---|
652b7e9 | Briana Mittleman | 2018-07-19 |
plot(gap_bppos,gap_res$est,type='l',xlab="position",ylab="intensity", main="SMASH results GAPDH")
Version | Author | Date |
---|---|---|
652b7e9 | Briana Mittleman | 2018-07-19 |
sessionInfo()
R version 3.4.2 (2017-09-28)
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/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/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] dplyr_0.7.5 workflowr_1.0.1 rmarkdown_1.8.5 tidyr_0.7.2
[5] smashr_1.2-0 scales_0.5.0 devtools_1.13.6
loaded via a namespace (and not attached):
[1] Rcpp_0.12.17 bindr_0.1.1 pillar_1.1.0
[4] compiler_3.4.2 git2r_0.21.0 plyr_1.8.4
[7] R.methodsS3_1.7.1 R.utils_2.6.0 bitops_1.0-6
[10] iterators_1.0.10 tools_3.4.2 digest_0.6.15
[13] tibble_1.4.2 evaluate_0.10.1 memoise_1.1.0
[16] lattice_0.20-35 pkgconfig_2.0.1 rlang_0.2.1
[19] Matrix_1.2-12 foreach_1.4.4 yaml_2.1.19
[22] parallel_3.4.2 bindrcpp_0.2.2 withr_2.1.1
[25] stringr_1.3.1 knitr_1.18 caTools_1.17.1
[28] tidyselect_0.2.4 rprojroot_1.3-2 grid_3.4.2
[31] glue_1.2.0 data.table_1.11.4 R6_2.2.2
[34] purrr_0.2.5 ashr_2.2-7 magrittr_1.5
[37] whisker_0.3-2 backports_1.1.2 codetools_0.2-15
[40] htmltools_0.3.6 MASS_7.3-48 assertthat_0.2.0
[43] colorspace_1.3-2 wavethresh_4.6.8 stringi_1.2.2
[46] munsell_0.4.3 doParallel_1.0.11 pscl_1.5.2
[49] truncnorm_1.0-8 SQUAREM_2017.10-1 R.oo_1.22.0
This reproducible R Markdown analysis was created with workflowr 1.0.1