<p>This is described briefly in <a href="https://www.nature.com/articles/s41467-019-11994-0" rel="nofollow noreferrer">the paper</a>. The four quantities are inputs to the estimator of model accuracy:</p>

<ul>
<li><code>nres</code> is the sequence length.</li>
<li><code>neff</code> is an effective sequence count, or how deep the alignment was.</li>
<li><code>dpscore</code> is how well the final model matches the initial distance prediction.</li>
<li><code>dpscorenorm</code> is a normalised version of the above.</li>
</ul>

<p>Don't worry too much about directly interpreting these. They are only given for completion. The important line is <code>Estimated TM-score of ../final_1.pdb is 0.5</code>, indicating that DMPfold just about thinks this is a decent model.</p>

<p>The "sequence.ema.txt" is more raw output giving the probability of the TM-score being in each bin. "rawdistpred.1" is the distance predictions from the first iteration. Always use "rawdistpred.1" as input to the TM-score predictor as this is how it was trained.</p>

CC BY-SA 4.0
2019-09-24T10:24:26.753Z
2019-09-24T10:24:26.753Z
jgreener
<p>So, my runs have finished and got 5 final models. I predicted TM-score of one model to understand the result. The output of "predict-tmscore.sh" for "final_1.pdb" is:</p>

<pre><code>1 models read from PDB file
1 models read from PDB file
nres is 377
neff is 15423
dpscore is -300.599030
dpscorenorm is -0.082424
Probability of each TM-score bin (cols 1-10), estimated TM-score (col 11) and prob TM &gt; 0.5 (col 12) written to sequence.ema.txt
Estimated TM-score of ../final_1.pdb is 0.5
</code></pre>

<p>could you please help me understand what does "nres", "neff", "dpscore", and "dpscorenorm" below mean: </p>

<pre><code>    nres is 377 
neff is 15423 
dpscore is -300.599030 
dpscorenorm is    -0.082424
</code></pre>

<p>and it also generates a "sequence.ema.txt" file with below value:</p>

<pre><code>2.0308916646172293e-05 2.0682286958617624e-06 0.04564645141363144 0.14857041835784912 0.27177685499191284 0.31814685463905334 0.19150513410568237 0.022412151098251343 0.001872337656095624 4.743059980683029e-05 0.5036169363265117 0.5339840054512024
</code></pre>

<p>Please let me know what these above values signify?</p>

<p>And,I would really appreciate your comments on what does "rawdistpred.1" file mean? There are total 9 such files. When predicitng TM-score, do I need to use "rawdistpred.1" file for all final models or I can use any "rawdistpred.*" file? </p>

<p>thanks!   </p>

CC BY-SA 4.0
2019-09-24T10:50:51.647Z
Excellent question and answers on two core structure prediction programs
M__
<protein-structure>
What does final generated models with TM-score of DMPfold signify in "sequence.ema.txt" file?
# What does final generated models with TM-score of DMPfold signify in "sequence.ema.txt" file?

(Asked by: username_0 on 2019-09-24)

So, my runs have finished and got 5 final models. I predicted TM-score of one model to understand the result. The output of "predict-tmscore.sh" for "final_1.pdb" is:
1 models read from PDB file
1 models read from PDB file
nres is 377
neff is 15423
dpscore is -300.599030
dpscorenorm is -0.082424
Probability of each TM-score bin (cols 1-10), estimated TM-score (col 11) and prob TM > 0.5 (col 12) written to sequence.ema.txt
Estimated TM-score of ../final_1.pdb is 0.5

could you please help me understand what does "nres", "neff", "dpscore", and "dpscorenorm" below mean: 
    nres is 377 
neff is 15423 
dpscore is -300.599030 
dpscorenorm is    -0.082424

and it also generates a "sequence.ema.txt" file with below value:
2.0308916646172293e-05 2.0682286958617624e-06 0.04564645141363144 0.14857041835784912 0.27177685499191284 0.31814685463905334 0.19150513410568237 0.022412151098251343 0.001872337656095624 4.743059980683029e-05 0.5036169363265117 0.5339840054512024

Please let me know what these above values signify?
And,I would really appreciate your comments on what does "rawdistpred.1" file mean? There are total 9 such files. When predicitng TM-score, do I need to use "rawdistpred.1" file for all final models or I can use any "rawdistpred.*" file? 
thanks!

**Tags:** protein-structure
> **Comments:**
> **username_1**: Excellent question and answers on two core structure prediction programs  

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## 1 answers

### Answer by username_2 on 2019-09-24. Score: 2 | Accepted answer

This is described briefly in [the paper](https://www.nature.com/articles/s41467-019-11994-0). The four quantities are inputs to the estimator of model accuracy:

* `nres` is the sequence length.
* `neff` is an effective sequence count, or how deep the alignment was.
* `dpscore` is how well the final model matches the initial distance prediction.
* `dpscorenorm` is a normalised version of the above.

Don't worry too much about directly interpreting these. They are only given for completion. The important line is `Estimated TM-score of ../final_1.pdb is 0.5`, indicating that DMPfold just about thinks this is a decent model.

The "sequence.ema.txt" is more raw output giving the probability of the TM-score being in each bin. "rawdistpred.1" is the distance predictions from the first iteration. Always use "rawdistpred.1" as input to the TM-score predictor as this is how it was trained.


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