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File Version Author Date Message
html 0398fdb Briana Mittleman 2018-07-25 Build site.
Rmd 2d41f11 Briana Mittleman 2018-07-25 add expand smash to index

I want to run smash on a whole chromosome to see what regions I can do it on to get the whole genome. First I am going to try chromosome 22.

Prepare data

I want to create a bedgraph for the combined nuclear and total files.

  • /project2/gilad/briana/threeprimeseq/data/macs2/TotalBamFiles.sort.bam

  • /project2/gilad/briana/threeprimeseq/data/macs2/NuclearBamFiles.bam

#!/bin/bash

#SBATCH --job-name=5gencov_comb
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=5gencov_comb.out
#SBATCH --error=5gencov_com.err
#SBATCH --partition=broadwl
#SBATCH --mem=40G
#SBATCH --mail-type=END


module load Anaconda3
source activate three-prime-env 



bedtools genomecov -d -5 -ibam  /project2/gilad/briana/threeprimeseq/data/macs2/TotalBamFiles.sort.bam   > /project2/gilad/briana/threeprimeseq/data/genomecov/gencov5prime.combinedTotal.bed

bedtools genomecov -d -5 -ibam  /project2/gilad/briana/threeprimeseq/data/macs2/NuclearBamFiles.sort.bam > /project2/gilad/briana/threeprimeseq/data/genomecov/gencov5prime.combinedNuclear.bed

I now need to subset the bed files to chr22.

#!/bin/bash

#SBATCH --job-name=subset22
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=subset22.out
#SBATCH --error=subset22.err
#SBATCH --partition=broadwl
#SBATCH --mem=40G
#SBATCH --mail-type=END


module load Anaconda3
source activate three-prime-env 


awk '$1==22 {print}' /project2/gilad/briana/threeprimeseq/data/genomecov/gencov5prime.combinedNuclear.bed > /project2/gilad/briana/threeprimeseq/data/genomecov_chr22/gencov5prime.combinedNuclear.chr22.bed


awk '$1==22 {print}' /project2/gilad/briana/threeprimeseq/data/genomecov/gencov5prime.combinedTotal.bed > /project2/gilad/briana/threeprimeseq/data/genomecov_chr22/gencov5prime.combinedTotal.chr22.bed

Run smash

Chromosome 22 is 51304566 bases. I need this to satisfy the \(2^{x}\) criteria. I can use the log rule, \(log_{2}length=x\)

log2(51304566)
[1] 25.61258
2^26
[1] 67108864
zeros_to_add=67108864 -51304566

I will use 2^26, 67108864. This means I need to add 1.580429810^{7} 0s to the matrix. I can do this by making a matrix with the correct number of zeros and row binding it.

zero_matrix=matrix(0.1, zeros_to_add)

I will write and R script that I can run on the cluster. The file will take in the genomecoverage file and will output the graph and the smash results in a bedgraph format.

#!/bin/rscripts

# usage: ./run_smash.R gencoverage, outfile_plot, outfile_bedgraph

#this script takes the genomecov file and a name for an output plot (.png) and an output bedgraph (.bg)

#use optparse for management of input arguments I want to be able to imput the 6up nuc file and write out a filter file  

#script needs to run outside of conda env. should module load R in bash script when I submit it 
library(optparse)
library(dplyr)
library(tidyr)
library(ggplot2)
library(scales)
library(smashr)


option_list = list(
  make_option(c("-f", "--file"), action="store", default=NA, type='character',
              help="input file"),
  make_option(c("-p", "--plot"), action="store", default=NA, type='character',
              help="output plot file"),
  make_option(c("-o", "--output"), action="store", default=NA, type='character',
              help="output file")
)
  

opt_parser <- OptionParser(option_list=option_list)
opt <- parse_args(opt_parser)


#interrupt execution if no file is  supplied
if (is.null(opt$file)){
  print_help(opt_parser)
  stop("Need input file", call.=FALSE)
}



#Functions for this script


criteria=function(x){
  #function takes a number and makes the matrix with 0s
  exp=log2(x)
  exp_round=ceiling(exp)
  zerosadd= 2^exp_round - x
  seq_0=rep(0, zerosadd)
  return(seq_0)
}


#import bedgraph
names=c("Chr", "Pos", "Count")
cov=read.table(file = opt$file,  col.names = names)

chromosome=cov[1,1]


#prepare data by adding 0s
zero_seq=criteria(nrow(cov))
data_vec=as.vector(cov$Count)
data_zero_vec=c(data_vec, zero_seq)
data_zero_matrix=matrix(data_zero_vec, 1, length(data_zero_vec))

#run smash

smash_res=smash.poiss(data_zero_matrix[1,],post.var=TRUE)


#create and save plot
pos=1:length(data_vec)
png(opt$plot)
finalplot=plot(pos,smash_res$est[1:length(data_vec)],type='l',xlab="position",ylab="intensity", main="SMASH results")
dev.off()

#create bedgraph and write it out  

bedgraph=cbind(lapply(cov$Chr, function(x) paste("chr", x, sep="")), cov$Pos, cov$Pos + 1,  smash_res$est[1:length(data_vec)])

write.table(bedgraph, file=opt$output, quote = F, row.names = F, col.names = F)

To run this I will have to create a batch script similar to the following.

#!/bin/bash

#SBATCH --job-name=run.run_smash
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=run_runsmash.out
#SBATCH --error=run_runsmash.err
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END

module load R

Rscript run_smash.R -f /project2/gilad/briana/threeprimeseq/data/genomecov_chr22/gencov5prime.combinedTotal.chr22.bed -p /project2/gilad/briana/threeprimeseq/data/smash.chr22/smooth.combinedTotal.chr22.png -o /project2/gilad/briana/threeprimeseq/data/smash.chr22/smooth.combinedTotal.chr22.bg





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_1.2.0 Rcpp_0.12.19    digest_0.6.17   rprojroot_1.3-2
 [5] backports_1.1.2 git2r_0.24.0    magrittr_1.5    evaluate_0.13  
 [9] stringi_1.2.4   fs_1.2.6        whisker_0.3-2   rmarkdown_1.11 
[13] tools_3.5.1     stringr_1.4.0   glue_1.3.0      yaml_2.2.0     
[17] compiler_3.5.1  htmltools_0.3.6 knitr_1.20