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Last update on 04. Mar 2022 .
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Estimate Parameters from Column Statistics





In a standard RNA, base frequencies are not equally distributed. Especially in the archea subclass we find extremely G+C rich sequences. This yielded in a couple of new rate corrections, algorithms and programs which:

  • calculate the average G+C content of all/two sequences
  • correct the distance.

But further research showed us that the G+C frequencies are not equally distributed within a sequence. Especially helical parts have a significant higher G+C content than non helical parts. One strait forward algorithm would calculate each frequency independently for each column. Especially for small datasets the resulting frequencies would look like random data, as too few examples are analyzed.

In ARB we implemented a combination of the 2 approaches. Lets say we want to estimate a Parameter 'P' with a maximum variance 'maxvar', so we need a minimum samples 'minsap'.

  • All sequence positions are clustered according to
    • helical/non helical region
    • variability

    The size of the cluster is choosen with respect to the variability of the sequences to get a minimum of independent events.
  • The final parameter estimate for a column is a weighted sum between the estimate for the cluster and the estimate for the single position.

You can give your favorite method a higher weight by controlling the smoothing parameter:

Less smoothing -> independent parameter estimates
Much smoothing -> clustered parameter estimates

To get a good tree we recommend you to try all selections.



To get parameters from a column statistic you first have to create one. Do this with <ARB_NT/SAI/Positional Variability (Parsimony M.)>



Problems may occur when

  1. 'independent parameter estimates' is selected and
  2. your dataset is quite small (<100 Sequences) and
  3. one sequence is bad or badly aligned


  1. Much smoothing of parameters is selected and
  2. you are analyzing ribosomal RNA and
  3. 'Use Helix Information' is turned off



No bugs known