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<h1 class="title toc-ignore">Mispriming Approach</h1>
<h4 class="author"><em>Briana Mittleman</em></h4>
<h4 class="date"><em>1/11/2019</em></h4>
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<p><strong>Last updated:</strong> 2019-01-11</p>
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<a href="https://github.com/brimittleman/threeprimeseq/blob/42fcbdd1ff21ebf0e08b3df26501f37430f2290c/analysis/mispriming_approach.Rmd" target="_blank">42fcbdd</a>
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Briana Mittleman
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2019-01-11
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initialize mispriming approach file
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<p></details></p>
<hr />
<p>In this analysis I am gonig to explore the ways to handle mispriming in the 3’ seq data. Some people call this internal priming. This is when the polyDt primer attached to an RNA molecule that has a long stretch of A’s rather than to the tail. You can identify when this is happening because polyA tails are not in the genome but mispriming As are. In my data I need to look for Ts upstream of the read. This is because our reads are on the opposite strand.</p>
<p>Sheppard et al. cited 2 other papers, Beaudoing et al 2000 and Tian et al 2005. Thet excluded reads with 6 consequitive upstream As or those with 7 in a 10nt window. They did this at the read level.</p>
<p>I started thinking about this in <a href="https://brimittleman.github.io/threeprimeseq/filter_As.html" class="uri">https://brimittleman.github.io/threeprimeseq/filter_As.html</a>. I did not have it mapped out correctly because I was looking for A’s on one strand and T’s on the other.</p>
<p>I will assess the problem then will create a blacklist to get rid of the reads. I should do this in the snakefile before we create BW for the peak calling.</p>
<p>I can start by updating 6up_bed.sh. To make a new script that grabs the upstream 10 bases. I will look for7 of 10 T’s in this region. I am going to do this in python because it is more straight forward to read then an awk script. I can also wrap it easier this way. I can also account for negative values and values larger than the chromosome this way.</p>
<p>Upstream10Bases.py</p>
<pre class="bash"><code>#python
def main(Fin, Fout):
outBed=open(Fout, "w")
chrom_lengths=open("/project2/gilad/briana/genome_anotation_data/chrom_lengths2.sort.bed","r")
#make a dictionary with chrom lengths
length_dic={}
for i in chrom_lengths:
chrom, start, end = i.split()
length_dic[str(chrom)]=int(end)
#write file
for ln in open(Fin):
chrom, start, end, name, score, strand = ln.split()
chrom=str(chrom)
if strand=="+":
start_new=int(start)-10
if start_new <= 1:
start_new = 1
end_new= int(start)
outBed.write("%s\t%d\t%d\t%s\t%s\t%s\n"%(chrom, start_new, end_new, name, score, strand))
if strand == "-":
start_new=int(end)
end_new=int(end) + 10
if end_new >= length_dic[chrom]:
end_new = length_dic[chrom]
outBed.write("%s\t%d\t%d\t%s\t%s\t%s\n"%(chrom, start_new, end_new, name, score, strand))
outBed.close()
if __name__ == "__main__":
import sys
inFile = sys.argv[1]
fileNoPath=inFile.split("/")[-1]
fileshort=fileNoPath[:-4]
outFile="/project2/gilad/briana/threeprimeseq/data/bed_10up/" + fileshort + "10up.bed"
main(inFile, outFile)
</code></pre>
<p>I can wrap this for all of the files.<br />
wrap_Upstream10Bases.sh</p>
<pre class="bash"><code>#!/bin/bash
#SBATCH --job-name=w_Upstream10Bases
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=w_Upstream10Bases.out
#SBATCH --error=w_Upstream10Bases.err
#SBATCH --partition=broadwl
#SBATCH --mem=8G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
for i in $(ls /project2/gilad/briana/threeprimeseq/data/bed_sort/*-combined-sort.bed); do
python Upstream10Bases.py $i
done
</code></pre>
<p>Next step is running the nuc function to get the sequences of the positions I just put in the bed files.</p>
<p>bedtools nuc</p>
<ul>
<li><p>-fi (fasta file) /project2/gilad/briana/genome_anotation_data/genome/Homo_sapiens.GRCh37.75.dna_sm.all.fa</p></li>
<li><p>-bed results from 10up stream</p></li>
<li><p>-s strand specific</p></li>
<li><p>-seq print exracted sequence</p></li>
<li><blockquote>
<p>output</p>
</blockquote></li>
</ul>
<p>Nuc10BasesUp.sh</p>
<pre class="bash"><code>#!/bin/bash
#SBATCH --job-name=Nuc10BasesUp
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=Nuc10BasesUp.out
#SBATCH --error=Nuc10BasesUp.err
#SBATCH --partition=broadwl
#SBATCH --mem=36G
#SBATCH --mail-type=END
for i in $( ls /project2/gilad/briana/threeprimeseq/data/bed_10up/*);do
describer=$(echo ${i} | sed -e 's/.*YL-SP-//' | sed -e "s/-combined-sort10up.bed$//")
bedtools nuc -s -fi /project2/gilad/briana/genome_anotation_data/genome/Homo_sapiens.GRCh37.75.dna_sm.all.fa -bed $i > /project2/gilad/briana/threeprimeseq/data/nuc_10up/TenBaseUP.${describer}.txt
done</code></pre>
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<h2>Session information</h2>
<pre class="r"><code>sessionInfo()</code></pre>
<pre><code>R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.14.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] workflowr_1.1.1 Rcpp_0.12.19 digest_0.6.17
[4] rprojroot_1.3-2 R.methodsS3_1.7.1 backports_1.1.2
[7] git2r_0.23.0 magrittr_1.5 evaluate_0.11
[10] stringi_1.2.4 whisker_0.3-2 R.oo_1.22.0
[13] R.utils_2.7.0 rmarkdown_1.10 tools_3.5.1
[16] stringr_1.3.1 yaml_2.2.0 compiler_3.5.1
[19] htmltools_0.3.6 knitr_1.20 </code></pre>
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