Difference between revisions of "Matrix derivation (analysis)"

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Revision as of 19:00, 13 February 2017

Analysis title
Default-analysis-icon.png Matrix derivation
Provider
Institute of Systems Biology
Class
MatrixDerivation
Plugin
biouml.plugins.bindingregions (Binding-regions related analyses)

Description

Calculation of matrices by using mixture of normal components for scores of best sites in given sequence sample

Parameters:

  • Name of algorithm – Select name of algorithm
  • Type of site model – Select type of site model that will be used for matrix derivation
  • Window size – Window size
  • Are both strands? – Do analize both strands of sequences? (if 'no', then only strand (+) will be analyzed)
  • Path to table with sequence sample – Select path to table with sequence sample
  • Name of table column with sequence sample – Select name of table column with sequence sample
  • Parameters specific for 'Matrix derivation : successive algorithm based on 2-component normal mixtures' – Parameters specific for 'Matrix derivation : successive algorithm based on 2-component normal mixtures'
    • P-value threshold – P-value threshold
    • Number of matrices – How many matrices will be constructed
    • Initial approximation for matix – Define initial approximation for matix
      • Initial matrix approximation type – Select type of initial matrix approximation
      • Consensus – Specify the consensus
      • Matrix name – Define matrix name
      • Matrix path – Specify the path to the initial matrix
  • Parameters specific for 'Matrix derivation : EM-like algorithm for identification of several matrices simultaneously' – Parameters specific for 'Matrix derivation : EM-like algorithm for identification of several matrices simultaneously'
    • Score threshold – Score threshold
    • Initial approximations for matices – Define initial approximations for matices
  • Maximal number of iterations – Maximal number of iterations in algorithm
  • Path to output folder – Output folder will be created under this location when it doesn't exist
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