Piccolo

Program

• Program
  • Web application
  • Download the script file of a function for GNU Octave or MATLAB.

Example

• Data files for the script (Not for the web application)
  • GDS1629
  • GDS2110
  • GDS2232
  • GDS404
  • GSE3424
  • GSE6542_1
  • GSE6542_2
  • GSE6542_3
  • GSE6542_4
  • GSE6542_5
  • GSE6542_6
  • GSE6542_7

For the Web application, add a column which contains gene name, etc. to a head of each line of the data files above.

How to Use

• The GNU Octave/MATLAB script
  1. Install a recent version of GNU octave or MATLAB.
  2. Download piccolo.m and put somewhere you want. The desktop of your PC is easy to see.
  3. Put a dataset to be analyzed as a ascii text file in the directory where piccolo.m is put.
  4. Launch GNU octave or MATLAB, specify the directory above as the working directory.
  5. Load the data file. e. g. load mydata = data.txt;.
     data cannot contain anything but numerical data to be analyzed except header lines. A number of header lines to be skipped must be specified next step.
  6. call the function 'piccolo' as follows:
     function piccolo(rawdata, header=0, ic=1, interval=4)
     • rawdata: loaded input data
     • header: heading lines to be skipped
     • ic: information criterion to be used (1: AIC, 2: BIC)
     • interval: interval of time between each sampoing point

Useful Links

• Time series analysis
  • ARSER for identifying periodic expression profiles in analyzing microarray data (Web app)
  • STEM, Short Time-series Expression Miner
• General Genome Analysis
  • Software and Tools for Genome Analysis (Introduction for many tools, Japanese)

References

• Tominaga D, "Periodicity detection method for small-sample time series datasets", Bioinformatics and Biology Insights, 4, 127-136 (2010).
• Tominaga D. and K. Horimoto, "Judgment alforithm for periodicity of time series data based on bayesian information criterion", Journal of Bioinformatics and Computational Biology, 6(4), 747-757 (2008).