• GUI Installer
  • GUI parameter settings
  • fiding MSTs
  • calculating degrees of each sequences
  • showing some analyses as graphs
    • distribution of degrees
    • distribution of tree size
    • composition of top 30 largest trees.


Goto Download site.

How To Install


  1. Download a msi package.
  2. Double-click the package to launch Windows installation wizard.


  1. Download tar.gz file which is appropriate to your PC, and uncompress the archives.
  2. Execute following commands to launch installation wizard.
    cd VisualSlideSort-1.0



  • comming soon.

Drawing graphs without connection of internet

  • Graphs in summary panel are not shown, if your PC is not connected to internet with default settings.
  • To enable Visual SLIDESORT to show graphs without internet connection, highcharts.js and jquery-1.4.2.js are required to be placed in Resource directory (install_dir/Resources/import/).
  • If you are a non-commercial user, you can freely download highcharts.js from (see definition of License for detail information)
  • jquery-1.4.2.js is available from (see the definition of lisence for detail information)
  • Please download and use them at your own risk.

Input File Format

  • SLIDESORT accepts multi-fasta format.
  • User can choose DNA sequence or Protein Sequence.
  • See wikipedia for detailed explanation.

Execution with Normal Mode

Parameter setting & execution

  1. Input or select fasta file.
    • Click a hand lens icon to launch a file select window.
  2. Input or select output tree file name for outputting minimam spanning trees.
  3. Input or select file name for outputting degree.
    • Visual SLIDESORT calculate exact number of neighbours (degree) for each sequence.
  4. Select distance type (Hamming or Edit).
    • Hamming distance
    • Edit distance
      • Default setting calcurate Levenshtein distance (gap extension cost=1, gap openning cost=0). User can freely set gap cost.
  5. Input distance threshold
  6. Input gap cost
    • gap extension cost.
    • gap openning cost.
    • (Example) Edit distance with gap extension cost=1.2, gap openning cost=0.3 of the following alignment is 1.2×3+0.3×2=4.2
  7. Click "ExecSlideSort?" to execute SlideSort.



  1. Jobs are shown in the bottom panel.
    • Click Job title to show the corresponding Job window.
  2. If the Calcuration is finished, "Show Summary" button is appeared in the Job window.


  3. Click "Show Summary" to show resutls summary.
  4. Click "Save as Text" to store all the information in text format.
  5. Click "Print" to print out the result summary window.



Execution with Advanced Mode

Advanced mode provide additional options.

  1. Parameter setting of neighbour pairs.
    1. Select if neighbour pairs should be written to the file or not.
    2. Select if the Alignment of the neighbour pair should be written to the file or not.
    • (IMPORTANT!!) These two options may cause huge size of file IO, if the number of input short reads are large (e.g. tens of million.). Please be careful of available disk size and notice that outputting huge file is time consuming.
    1. Input or select a filename for outputting pairs.
  2. Select type of strings (DNA or Protein)
  3. "Automatic File Name set"
    • This option enable the program to choose file name automatically, and users do not have to select or input file names each running.
      • degree file degree_jobid.txt
      • tree file trees_jobid.txt
      • pair file pairs_jobid.txt
  4. "Exclude seqs with unknown characters"
    • This option enables the program to exclude sequences with unknown characters such as "X", "z", "N", etc.
  5. Select comparison mode
    1. one dataset.
      • The program finds neighbour pairs from all the input sequences.
    2. two datasets
      • User can extract two datasets from the input fasta file. And the program finds neighbour pairs BETWEEN the two.



  • Kana Shimizu and Koji Tsuda "SlideSort:All pairs similarity search for short reads", Bioinformatics (2011) 27 (4): 464-470. open access article

  • Takeaki Uno "An Efficient Algorithm for Finding Similar Short Substrings from Large Scale String Data", Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, 2008, Volume 5012/2008 (PAKDD 2008), 345-356, published online

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Last-modified: 2011-02-09 (Wed) 10:05:04 (3747d). Site admin: Kana Shimizu