TITLE: No Title
AUTHORS: 

[DESCRIPTION]
<p>Demo for identifying marker genes using <a href="https://ribodb.univ-lyon1.fr/ribodb/ribodb-in.cgi" target="_blank">RiboDB</a>. </p>

[GUIDELINES]
<p>Why important?</p>
<ol>
<li>Identify novel taxonomic lineages</li>
<li>Understanding evolutionary processes (Speciation, Geography, Age of taxa, Endosymbiosis, Tree of Life…)</li>
<li>Predict function of novel genes (Dsr genes)</li>
</ol>
<p>An example:</p>
<p> </p>
<p><img id="s-mce-img" class="s-mce-img" src="https://s3.amazonaws.com/pr-journal/eavc2w6.png" width="500" data-src="https://s3.amazonaws.com/pr-journal/eavc2w6.png" data-ofn="Screen Shot 2016-07-13 at 11.17.49 AM.png" /></p>
<p> </p>
<p><img id="s-mce-img" class="s-mce-img" src="https://s3.amazonaws.com/pr-journal/eawc2w6.png" width="500" data-src="https://s3.amazonaws.com/pr-journal/eawc2w6.png" data-ofn="Screen Shot 2016-07-13 at 11.18.38 AM.png" /></p>
<p> </p>
<p>What to use?</p>
<ol>
<li>DNA</li>
<li>RNA</li>
<li>Protein</li>
</ol>
<p>Non-coding <strong>DNA</strong> regions: higher mutation rate</p>
<dl>
<dt>→ Rapid evolving sequences for close relatives</dt>
</dl>
<p><strong>Proteins:</strong> mutate slower (must maintain function)</p>
<dl>
<dt>→ Good for distantly related species</dt>
</dl>
<p>Types of alignments</p>
<ol>
<li>Pair-wise alignment</li>
<li>Multiple alignment</li>
<li>Local alignment (Identify sub-sequences sharing high similarity)</li>
<li>Global alignment (Align entire sequences, up to both ends of each sequence)</li>
<li>Structure-guided alignments (ie. 16s, Takes secondary structure into account)</li>
</ol>
<p>Problems: possible to align two sequences by different combination of gaps</p>
<p> </p>
<p><img id="s-mce-img" class="s-mce-img" src="https://s3.amazonaws.com/pr-journal/eaxc2w6.png" width="500" data-src="https://s3.amazonaws.com/pr-journal/eaxc2w6.png" data-ofn="Screen Shot 2016-07-13 at 11.22.40 AM.png" /></p>
<p> </p>
<p>Programs for alignments</p>
<ul>
<li>ARB (2nd structure)</li>
<li>MUSCLE</li>
<li>Geneious</li>
<li>MEGAN</li>
</ul>
<p>Tree construction methods</p>
<ul>
<li>Distance (Neighbour-joining)</li>
<li>Maximum Parsimony</li>
<li>Maximum Likelyhood (ML)</li>
<li>Bayesian</li>
</ul>
<p>Distance:</p>
<p>Calculate pairwise distances on alignment</p>
<p>Count number of differences between seqs</p>
<p>Phylogenetic tree calculated on distance matrix</p>
<p> </p>
<p>+ Fast (many seqs), good for first tree, ok when low distance between sequences</p>
<p>- Sequence info based on 1 parameter, does not account for multiple mutations at one site</p>
<p> </p>
<p><img id="s-mce-img" class="s-mce-img" src="https://s3.amazonaws.com/pr-journal/eayc2w6.png" width="500" data-src="https://s3.amazonaws.com/pr-journal/eayc2w6.png" data-ofn="Screen Shot 2016-07-13 at 11.26.23 AM.png" /></p>
<p> </p>
<p>Maximum parsimony:</p>
<p>All possible trees determined from each position of the sequence alignment</p>
<p>Each tree gets a score based on number of steps to generate tree</p>
<p>Chosen tree = min. nr. of mutations that could produce the data</p>
<p> </p>
<p>+ Uses all data, Good for close evol. distances</p>
<p>- Slow, assumes equal rate of mutations, many scenarios possible</p>
<p> </p>
<p>Maximum likelihood:</p>
<p>ML employs a model of evolution, i.e. different rates of transitions/transversion</p>
<p>Probability calculated how each position reflects sequencing data (for all 4 nucleotide sites)</p>
<p>Tree generated that is most likely to have produced the observed data is generated</p>
<p> </p>
<p>+ Model of evolution, uses all sequence info, corrects for multiple mutations → good for large evol. distances</p>
<p>- Very slow, depends on model of evolution used</p>
<p> </p>
<p>Bayesian:</p>
<p>Incorporation of prior information about a parameter</p>
<p>Then calculate the likelihood of a given site after observing some data (posterior probability)</p>
<p>Chose tree with highest posterior probability</p>
<p> </p>
<p>+ relatively fast, allows more complex models, gives both tree estimate and measure of uncertainty</p>
<p>- needs to specify prior information, very different run times for different trees</p>
<p> </p>
<p>Evolutionary models:</p>
<p>Interpreters of phylogenetic info in a sequence. Each model makes different basic assumptions.</p>
<p> </p>
<dl>
<dt>→ Which model for my data?</dt>
</dl>
<dl>
<dt>→ Did my model create reliable data?</dt>
</dl>
<ol>
<li>Aminoacid substitution model</li>
<li>Codon based models</li>
<li>Models depending on secondary structure</li>
</ol>
<p>Model selection:</p>
<p>jModelTest2: </p>
<p><a href="http://code.google.com/p/jmodeltest2/" target="_blank">http</a><a href="http://code.google.com/p/jmodeltest2/" target="_blank">://code.google.com/p/jmodeltest2</a><a href="http://code.google.com/p/jmodeltest2/" target="_blank">/</a></p>
<p><a href="http://jmodeltest.org/" target="_blank">http://jmodeltest.org</a><a href="http://jmodeltest.org/" target="_blank">/</a></p>
<p> </p>
<ul>
<li>Several selection criteria employing maximum likelihood (ML) scores</li>
<li>Free</li>
<li>Not ideal for Bayesian approaches</li>
</ul>
<p> </p>

[STEPS]
?. 
?. 
?. 
?. 
?. 
?. 
?. 
?. 
?. 
?.