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<title>Step 03 - Loading and Processing Protein Data</title>
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<h1>Step 03 - Loading and Processing Protein Data</h1>
<h2>Motivation</h2>
<p>Now that I've decided to use the reference-aligned data, all I need to do before I can merge the data is to extract the unique protein reads from <code>data/203.prot.fa</code> that match perfectly to the DNA sequences in the library. I have similar code written already that I used for the non-reference aligned code.</p>
<p>It works in three steps. We could also use <code>grep</code>, but this is faster computationally, and I already have the code written.</p>
<ol>
<li>Since there are only 280 promo/cds combos, and I have a file containing
them, I will filter on those first. </li>
<li>We use bowtie to quickly align the Protein to the DNA, similar to how we did the RNA. In this case, we will only keep protein data that matches exactly. </li>
<li>Because bowtie finds partial matches, we use a perl regexp to parse out the reads that are complete (by looking for a full length promoter, RBS, and CDS.)</li>
</ol>
<h2>Running Bowtie</h2>
<blockquote>
<p>Bowtie Settings:<br/>
<code>-k 280</code>: report up to 280 alignments per contig (280 promo/rbs combos)<br/>
<code>-v 0</code>: 0 mismatches per contig (no indels)<br/>
<code>-l 10</code>: seed length of 10<br/>
<code>-p 16</code>: use all 16 processors<br/>
<code>-m 1</code>: throw away reads that do not match to one sequence only</p>
</blockquote>
<pre><code class="bash">#perform bowtie for Protein. Afterwards, remove from that output any protein
#reads that are not complete matches
#build the bowtie index
mkdir data/03_load_prot
/opt/bowtie/bowtie-build data/203.norestrict.fa data/03_load_prot/203
/opt/bowtie/bowtie -v 0 -l 10 -k 280 -p 2 -m 1 \
--norc --best --strata --suppress 2,6 \
--un data/203.prot.unmapped.fa -f data/03_load_prot/203 \
<(gzcat data/203.prot.fa.gz | grep -B1 -if data/all_promo_rbs.txt \
| grep -v '\--') \
| perl -ne '/([ATGC]{40})([ATGC]{18,21})(ATG[ATGC]{30})/
&& print;' > data/203.prot.bowtie
## reads processed: 60188
## reads with at least one reported alignment: 15879 (26.38%)
## reads that failed to align: 44111 (73.29%)
## reads with alignments suppressed due to -m: 198 (0.33%)
## Reported 15879 alignments to 1 output stream(s)
wc -l data/203.prot.bowtie
## 14140 (down from 15879 due to checking for partial aligns with perl pipe)
</code></pre>
<p>Out of 14,234 possible sequences, we got 14,140 with protein reads. 94 constructs have no Protein reads. Let's read them into R and take a look. The <code>load_raw_reads</code> function comes from step 02.</p>
<pre><code class="r">col.names = c("Read.num", "Count", paste("Bin", c(1:12), sep = "."),
"Name", "Offset.L", "Read.seq", "Alts", "Mismatches")
prot.raw <- load_raw_reads(paste(getwd(), "data/203.prot.bowtie",
sep = "/"), is.rna = F, col.names = col.names)
</code></pre>
<h2>Conclusions</h2>
<h3>Summary of Missing Data</h3>
<p>We now have all the raw data. Before we start merging and calculating, we now can see how many constructs are missing from each data set. </p>
<ul>
<li><p><code>94</code> constructs missing from Protein:</p></li>
<li><p><code>17</code> constructs missing <br/>
from RNA</p></li>
<li><p><code>15</code> constructs missing <br/>
from DNA</p></li>
<li><p><code>15</code> constructs missing from both DNA and Protein </p></li>
<li><p>There is no overlap between missing RNA and DNA constructs. </p></li>
<li><p><strong><code>111</code></strong> costructs in total that are missing RNA, DNA, or Protein. </p></li>
</ul>
<p>This was pretty straightforward. Onto the merging and score calculation.</p>
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