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<p class="p1"><span class="s1">Hi Mohamed,</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p2"><span style="font-size: 10pt;">There are a number of of factors that influence how much model bias there is in a MR-SAD experiment. Additionally the model bias is different at different steps in the procedure. You also have several choices that
affect how much model bias there is:</span><span class="s1"></span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">Options for reducing model bias in MR-SAD initial phasing</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">1. Considering just the initial phasing step, you have two options in Phenix: </span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">A. You can find sites with phaser LLG maximization using your input model as part of the total model, then phase using the sites that you find and exclude the model in the phasing step. This is the keyword "phaser_sites_then_phase=True"
and it has essentially no model bias.</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">B. You can find sites and phase in one step with Phaser, in which case your phases will contain information from the model and there can be model bias. You get two different sets of HL coefficients, one is HLA etc, the other
is HLanomA etc. The first contains the same information in the phases, and may be biased by the model. The second does not contain phase information from the model, only from the anomalous differences. </span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">Options for reducing model bias in MR-SAD in density modification and refinement</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">2. Once you have obtained calculated phases and phase probabilities with and without the model (HL and HLanom), you have additional choices as to how to use this information. In all cases the starting phases are those from step
1, and include model information unless you set phaser_sites_then_phase=True. The choices in this stage consist of whether to use the phase probabilities with model information (HL) or without (HLanom).</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">A. You can specify whether to use phase probabilities with or without the model in density modification and refinement. If you set use_hl_anom_in_denmod=False (default) then model information will be used in density modification.
If you set use_hl_anom_in_denmod=True then HLanom coefficients not including model information will be used. </span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">B. You can separately specify whether to use model information in refinement. If you set use_hl_anom_in_refinement=True (default if a partial model has been supplied as in MR-SAD), then phase probabilities without the model will
be used.</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">Avoiding model bias in MR-SAD</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">You can avoid model bias in MR-SAD completely with phaser_sites_then_phase=True. You can also have reduced model bias if you set use_hl_anom_in_denmod=True and use_hl_anom_in_refinement=True. If you do not reduce model bias
in one of these ways, the amount of bias is going to depend very much on the strength of the anomalous signal, the amount of solvent, and the resolution, as all of these factors contribute to the phase information coming from somewhere other than the model.</span></p>
<p class="p2"><span class="s1"></span><br>
</p>
<p class="p1"><span class="s1">A good way to check on model bias in this or any other case is to remove a part of your starting model (say, a helix) that you are worried about, and use that omit model in the whole procedure. Then if the density shows up in
the end for this feature you can be sure it is not due to model bias. You can do this after the fact � you solve your structure, you are worried that something in the map is model bias, you run the whole thing over starting with a model that does not have
this feature, it comes back in your maps, and you know it is ok. You can show the resulting map to anyone and they will know that it is not biased as well.</span></p>
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<div>All the best,</div>
<div>Tom T</div>
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<div id="divRpF531070" style="direction:ltr"><font face="Tahoma" size="2" color="#000000"><b>From:</b> phenixbb-bounces@phenix-online.org [phenixbb-bounces@phenix-online.org] on behalf of mohamed noor [mohamed.noor34@gmail.com]<br>
<b>Sent:</b> Friday, June 05, 2015 9:30 AM<br>
<b>To:</b> PHENIX user mailing list<br>
<b>Subject:</b> [phenixbb] Model bias in MR-SAD<br>
</font><br>
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<div>Dear all<br>
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In the case of MR-SAD, how bad can model bias be? Does it also depend on the data resolution and resolution at which there is still enough anomalous signal? Or can the anomalous signal help in overcoming the bias inherent in the MR model?<br>
<br>
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Thanks.<br>
<div><br>
<br>
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