Last updated: 2018-07-19

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    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.

Create Coverage files

#!/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

Test example region

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
Objective fn: 17138.8  Extrapolation: 1  Steplength: 4.55255
Objective fn: 16836.6  Extrapolation: 1  Steplength: 1.86253
Objective fn: 16818.8  Extrapolation: 1  Steplength: 6.42316
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
Objective fn: 31019  Extrapolation: 1  Steplength: 2.24046
Objective fn: 31004.3  Extrapolation: 1  Steplength: 5.95071
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
Objective fn: 43183.7  Extrapolation: 1  Steplength: 4.56042
Objective fn: 41597.4  Extrapolation: 1  Steplength: 1.93991
Objective fn: 41582.5  Extrapolation: 1  Steplength: 7.15247
Objective fn: 41416.1  Extrapolation: 1  Steplength: 1.69043
Objective fn: 41408.8  Extrapolation: 1  Steplength: 9.74108
Objective fn: 41406.9  Extrapolation: 1  Steplength: 1.59935
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
Objective fn: 39112.5  Extrapolation: 1  Steplength: 1.9387
Objective fn: 38929.7  Extrapolation: 1  Steplength: 4
Objective fn: 38852.8  Extrapolation: 1  Steplength: 1.89245
Objective fn: 38845.6  Extrapolation: 1  Steplength: 5.02972
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
Objective fn: 99983.8  Extrapolation: 1  Steplength: 3.04432
Objective fn: 99154  Extrapolation: 1  Steplength: 4.6448
Objective fn: 98661.4  Extrapolation: 1  Steplength: 2.95052
Objective fn: 98391.1  Extrapolation: 1  Steplength: 5.09439
Objective fn: 98302.4  Extrapolation: 1  Steplength: 2.05767
Objective fn: 98288.2  Extrapolation: 1  Steplength: 13.5878
Objective fn: 98224.6  Extrapolation: 1  Steplength: 1.53983
Objective fn: 98212.4  Extrapolation: 1  Steplength: 16
Objective fn: 98207  Extrapolation: 1  Steplength: 2.54441
Objective fn: 98203.1  Extrapolation: 1  Steplength: 8.20699
Objective fn: 98202  Extrapolation: 1  Steplength: 2.00162
Objective fn: 98199.8  Extrapolation: 1  Steplength: 16.5155
Objective fn: 98198.5  Extrapolation: 1  Steplength: 1.62338
Objective fn: 98199  Extrapolation: 1  Steplength: 44.8518
Objective fn: 98195.9  Extrapolation: 1  Steplength: 1.4749
Objective fn: 98195.6  Extrapolation: 0  Steplength: 1
Objective fn: 98195.4  Extrapolation: 0  Steplength: 1
Objective fn: 98195.2  Extrapolation: 0  Steplength: 1
Objective fn: 98195.1  Extrapolation: 0  Steplength: 1
Objective fn: 98194.8  Extrapolation: 1  Steplength: 16
Objective fn: 98194.6  Extrapolation: 0  Steplength: 1
Objective fn: 98194.5  Extrapolation: 0  Steplength: 1
Objective fn: 98194.4  Extrapolation: 0  Steplength: 1
Objective fn: 98194.2  Extrapolation: 1  Steplength: 16
Objective fn: 98194  Extrapolation: 0  Steplength: 1
Objective fn: 98193.9  Extrapolation: 0  Steplength: 1
Objective fn: 98193.7  Extrapolation: 1  Steplength: 16
Objective fn: 98193.6  Extrapolation: 0  Steplength: 1
Objective fn: 98193.5  Extrapolation: 0  Steplength: 1
Objective fn: 98193.4  Extrapolation: 0  Steplength: 1
Objective fn: 98193  Extrapolation: 1  Steplength: 16
Objective fn: 98192.9  Extrapolation: 0  Steplength: 1
Objective fn: 98192.8  Extrapolation: 0  Steplength: 1
Objective fn: 98192.7  Extrapolation: 0  Steplength: 1
Objective fn: 98192.1  Extrapolation: 1  Steplength: 16
Objective fn: 98192  Extrapolation: 0  Steplength: 1
Objective fn: 98191.9  Extrapolation: 0  Steplength: 1
Objective fn: 98190.9  Extrapolation: 1  Steplength: 16
Objective fn: 98190.8  Extrapolation: 0  Steplength: 1
Objective fn: 98190.6  Extrapolation: 0  Steplength: 1
Objective fn: 98189.2  Extrapolation: 1  Steplength: 16
Objective fn: 98189  Extrapolation: 0  Steplength: 1
Objective fn: 98186.8  Extrapolation: 1  Steplength: 16
Objective fn: 98186.6  Extrapolation: 0  Steplength: 1
Objective fn: 98183.6  Extrapolation: 1  Steplength: 16
Objective fn: 98183.3  Extrapolation: 0  Steplength: 1
Objective fn: 98179.6  Extrapolation: 1  Steplength: 16
Objective fn: 98179.1  Extrapolation: 0  Steplength: 1
Objective fn: 98175  Extrapolation: 1  Steplength: 16
Objective fn: 98174.4  Extrapolation: 0  Steplength: 1
Objective fn: 98171  Extrapolation: 1  Steplength: 16
Objective fn: 98170.2  Extrapolation: 0  Steplength: 1
Objective fn: 98169.6  Extrapolation: 0  Steplength: 1
Objective fn: 98167.5  Extrapolation: 1  Steplength: 16
Objective fn: 98166.5  Extrapolation: 0  Steplength: 1
Objective fn: 98165.9  Extrapolation: 0  Steplength: 1
Objective fn: 98165.4  Extrapolation: 0  Steplength: 1
Objective fn: 98164.7  Extrapolation: 1  Steplength: 16
Objective fn: 98163.9  Extrapolation: 0  Steplength: 1
Objective fn: 98163.3  Extrapolation: 0  Steplength: 1
Objective fn: 98163  Extrapolation: 0  Steplength: 1
Objective fn: 98162.7  Extrapolation: 0  Steplength: 1
Objective fn: 98162.6  Extrapolation: 1  Steplength: 16
Objective fn: 98162.1  Extrapolation: 0  Steplength: 1
Objective fn: 98161.8  Extrapolation: 0  Steplength: 1
Objective fn: 98161.6  Extrapolation: 0  Steplength: 1
Objective fn: 98161.5  Extrapolation: 0  Steplength: 1
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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
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Objective fn: 98160.5  Extrapolation: 1  Steplength: 2.79295
Due to absence of package REBayes, switching to EM algorithm
Squarem-1
Objective fn: 687462
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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))

Expand here to see past versions of unnamed-chunk-9-1.png:
Version Author Date
0464829 Briana Mittleman 2018-07-17

plot(bppos,res$est,type='l',xlab="position",ylab="intensity")

Expand here to see past versions of unnamed-chunk-9-2.png:
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)

Test actb

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")

Expand here to see past versions of unnamed-chunk-15-1.png:
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")

Expand here to see past versions of unnamed-chunk-15-2.png:
Version Author Date
652b7e9 Briana Mittleman 2018-07-19
3193223 Briana Mittleman 2018-07-18

Test Gapdh

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")

Expand here to see past versions of unnamed-chunk-20-1.png:
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")

Expand here to see past versions of unnamed-chunk-20-2.png:
Version Author Date
652b7e9 Briana Mittleman 2018-07-19

Session information

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