SEQREP1 Documentation
  • Requirements
  • 0. Installation and start
  • 1. Encode sequences using SEQREP codes
  • 2. Train a SOM
  • 3. Map sequences into a trained SOM
  • 4. Classify sequences after training a SOM
  •  5. Reference

  • Requirements

  • To run SEQREP1 you need a Java interpreter. If you have none installed, you can download Sun Java Runtime Environment (JRE) from http://java.sun.com/j2se/1.4/download.html.
  • 0. Installation and start
  • Extract all the files from SEQREP1.zip into the same directory. At the command line, go to the directory where you saved the files and type 'java SEQREP1'. 

  • 1. Encode sequences using SEQREP codes

    1. Menu 'File' -> 'Open File...'. Select the file with the sequences in FASTA format. Classification of the sequences should be included in the comment line of each sequence. Classes are labeled with letters A-I after string '#&'. For example, to label one sequence with class D, you should insert somewhere in the comment line, '#&D'.
    2. In the main panel, under 'Code Scheme', choose the virtual potentials you want to use for coding.
    3. Menu 'Tools' -> 'Encode'
    4. If you want to train a Kohonen SOM, go to point 2.
    5. If you want to save the SEQREP codes, choose 'Save with classes' or 'Save with labels' under menu 'File'. (Labels here are the first characters of the comment lines).


    2. Train a SOM

    1. Follow steps a-c of point 1 to encode the sequences.
    2. Choose, in the main panel, the settings you want to use for training (network size, initial learning span, number of epochs).
    3. Click on 'Train Kohonen NN', in the main panel.
    4. After the training, for inspection of the weights at a given level, fill in the field below 'Show weights at level:' and click on the button.


    3. Map sequences into a trained SOM

    1. Encode (with the same virtual potentials that were used to train the SOM) the new sequences you want to map and save the SEQREP codes, as described in point 1.
    2. Click on 'Map Objects', in the main panel. You will be asked to specify the file with the SEQREP codes (the one you saved in a.).
    3. The SOM surface, with the new sequences mapped on it, will be displayed in a second window. The sequences are labeled with the first characters of the comment line (from the original FASTA file) or with the class specified in the original FASTA file, depending on how the SEQREP codes were saved.
    4. If more than 3 sequences are mapped on the same neuron, you should move the mouse over that neuron in order to display all the sequences at the right side of the window.


    4. Classify sequences after training a SOM

    1. Encode the new sequences (with the same virtual potentials that were used to train the SOM) and save the SEQREP codes, as described in point 1.
    2. In the main panel, click on 'Predict'. You will be asked to specify the file with the SEQREP codes (the one you saved in a.) and then the file in which you want to save the results.
    3. The resulting file will contain a list of the sequences with the respective classification. Each line corresponds to one sequence, with labels in the first column, coordinates of the winning neuron in the second and third, and predicted classifications in the last column. If the classification is undecided it will be shown with letter 'J'.
    5. Reference
    • J. Aires-de-Sousa, L. Aires-de-Sousa, “Representation of DNA sequences with virtual potentials (SEQREP) and their processing by Kohonen self-organizing maps”, Bioinformatics, 2003, 19(1), 30-36.

    © 2002 João Aires de Sousa

    Copyright and Disclaimer SEQREP1 software is copyright © 2002 by Dr. Joao Aires de Sousa (jas@mail.fct.unl.pt). All rights reserved. Dr. Joao Aires de Sousa provides the accompanying software "as-is", without warranties of any kind; even including the implied warranty of fitness or merchantability for any particular purpose. Dr. Joao Aires de Sousa herein expressly disclaims all warranties on this software, either express or implied. Dr. Joao Aires de Sousa may not be held liable for any damages, incidental or consequential, occuring from the use of the accompanying software, even if he has been advised of the possibility of such damage.