text: user180: I have a list of regions of the human genome and I want to predict if single-stranded molecules in a buffer would tend to fold and create pin structures by sequence self-complementarity. What's the most precise software/parameter set I can use to such effect?
  TRIED SO FAR:
  Vienna RNALFold (unsure if applying an RNA software to DNA is adequate):
  Compute locally stable RNA secondary structure with a maximal base pair span. 
  For a sequence of length n and a base pair span of L the algorithm uses only 
  O(n+L*L) memory and O(n*L*L) CPU time. Thus it is practical to "scan" very 
  large genomes for short RNA structures.
  Output consists of a list of secondary structure components of size <= L, one 
  entry per line. Each output line contains the predicted local structure its 
  energy in kcal/mol and the starting position of the local structure.
  
  Example:
  samtools faidx $ref $region | seqtk seq -A - | $HOME/viennarna/bin/RNALfold --noconv
  >chr1:100000-100150
  .((((.(......).)))). ( -2.70)  127
  .(((.((........)).))). ( -5.70)  123
  .(((((((.((........)).)))..)))). ( -6.30)  119
  .(((.(.(((.((.....))))).)..))). ( -7.00)  117
  .((((.((........)).)))). ( -8.30)  109
  .((((..((.((..(..(((.....)))..)..)))))))). (-10.10)  103
  .((((.((..((..(((...((((.((........)).)))).....)))))..)))))). (-10.50)   90
  .((.((.((((....................)))).)).)). ( -4.10)   77
  .((((.((.((((....................)))).)).)))). ( -5.70)   75
  .((((..((((.((....)).)))).)))). ( -2.40)   72
  .((.((..((((..((((.((....)).)))).))))..)))). ( -5.50)   65
  .(.((..(..................((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).)))).)..)).). (-16.20)   40
  .((((......(.((..(..................((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).)))).)..)).).....)))). (-18.10)   30
  .(((....(((((((((...(.........)..)))).)))))((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).))))......))). (-18.50)   23
  .((....(((....(((((((((...(.........)..)))).)))))((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).))))......)))....)). (-18.70)   17
  .(((((((((......((...(((((..((((...((...))....))))..)))))...))......))))))))). ( -9.60)    7
  .((.(((((((((......((...(((((..((((...((...))....))))..)))))...))......))))))))).)). (-10.90)    4
  .(((..(((((........)))))..))). ( -3.60)    1
  ACTTAAGTTGTAGAAGGGAATAACGCAAGAGTGAATTTAGGGCGGGGCAAAAGGATAAATTTTACGGTACAAAGTTTCTACGGGTTTATATATGTATAACTAAGTCCAAGCGCGGGGGATATGGCCAGTGCACAACGGCGGGCATCATAAT
   (-21.70)
  
  
  user829: You could also take a look at Infernal.
  I think your best bet is to use RNA-focused programs; I'm not aware of a DNA-specific one, which makes some sense because DNA is typically double-stranded, so the secondary structure community is primarily focused on RNA. I would predict that secondary structure potential of single-stranded DNA would be similar to that of RNA.
  
original_text: 180: <p>I have a list of regions of the human genome and I want to predict if single-stranded molecules in a buffer would tend to fold and create pin structures by sequence self-complementarity. What's the most precise software/parameter set I can use to such effect?</p>
  
  <p>TRIED SO FAR:
  <a href="https://www.tbi.univie.ac.at/RNA/RNALfold.1.html" rel="nofollow noreferrer">Vienna RNALFold</a> (unsure if applying an RNA software to DNA is adequate):</p>
  
  <pre><code>Compute locally stable RNA secondary structure with a maximal base pair span. 
  For a sequence of length n and a base pair span of L the algorithm uses only 
  O(n+L*L) memory and O(n*L*L) CPU time. Thus it is practical to "scan" very 
  large genomes for short RNA structures.
  Output consists of a list of secondary structure components of size &lt;= L, one 
  entry per line. Each output line contains the predicted local structure its 
  energy in kcal/mol and the starting position of the local structure.
  </code></pre>
  
  <p>Example:</p>
  
  <pre><code>samtools faidx $ref $region | seqtk seq -A - | $HOME/viennarna/bin/RNALfold --noconv
  &gt;chr1:100000-100150
  .((((.(......).)))). ( -2.70)  127
  .(((.((........)).))). ( -5.70)  123
  .(((((((.((........)).)))..)))). ( -6.30)  119
  .(((.(.(((.((.....))))).)..))). ( -7.00)  117
  .((((.((........)).)))). ( -8.30)  109
  .((((..((.((..(..(((.....)))..)..)))))))). (-10.10)  103
  .((((.((..((..(((...((((.((........)).)))).....)))))..)))))). (-10.50)   90
  .((.((.((((....................)))).)).)). ( -4.10)   77
  .((((.((.((((....................)))).)).)))). ( -5.70)   75
  .((((..((((.((....)).)))).)))). ( -2.40)   72
  .((.((..((((..((((.((....)).)))).))))..)))). ( -5.50)   65
  .(.((..(..................((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).)))).)..)).). (-16.20)   40
  .((((......(.((..(..................((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).)))).)..)).).....)))). (-18.10)   30
  .(((....(((((((((...(.........)..)))).)))))((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).))))......))). (-18.50)   23
  .((....(((....(((((((((...(.........)..)))).)))))((.((..((((..((((.((....)).)))).))))..))))..((((.((........)).))))......)))....)). (-18.70)   17
  .(((((((((......((...(((((..((((...((...))....))))..)))))...))......))))))))). ( -9.60)    7
  .((.(((((((((......((...(((((..((((...((...))....))))..)))))...))......))))))))).)). (-10.90)    4
  .(((..(((((........)))))..))). ( -3.60)    1
  ACTTAAGTTGTAGAAGGGAATAACGCAAGAGTGAATTTAGGGCGGGGCAAAAGGATAAATTTTACGGTACAAAGTTTCTACGGGTTTATATATGTATAACTAAGTCCAAGCGCGGGGGATATGGCCAGTGCACAACGGCGGGCATCATAAT
   (-21.70)
  </code></pre>
   829: <p>You could also take a look at <a href="http://eddylab.org/infernal/" rel="nofollow noreferrer">Infernal</a>.</p>
  
  <p>I think your best bet is to use RNA-focused programs; I'm not aware of a DNA-specific one, which makes some sense because DNA is typically double-stranded, so the secondary structure community is primarily focused on RNA. I would predict that secondary structure potential of single-stranded DNA would be similar to that of RNA.</p>
  