Jan 102014
 

sppPCA 1.0

:: DESCRIPTION

The sppPCA method presented here provides an approach for researchers to perform exploratory data analysis on new -omic datasets containing missing data. By removing the necessity to impute missing values, the results of the low-dimensional projections of the data are not skewed by inaccurate estimates of variance, which is often introduced by imputation. Sequential projection pursuit (SPP) is a computationally robust approach for performing the optimization task to identify the small subset of orthogonal latent variables of interest (e.g., principal components).

:: DEVELOPER

Computational Biology & Bioinformatics ,Pacific Northwest National Laboratory

:: SCREENSHOTS

sppPCA

:: REQUIREMENTS

  • Windows
  • Matlab
  • JAVA

:: DOWNLOAD

 sppPCA

:: MORE INFORMATION

Citation

Biotechniques. 2013 Mar;54(3):165-8. doi: 10.2144/000113978.
Sequential projection pursuit principal component analysis–dealing with missing data associated with new -omics technologies.
Webb-Robertson BJ, Matzke MM, Metz TO, McDermott JE, Walker H, Rodland KD, Pounds JG, Waters KM.

157 views

Sorry, the comment form is closed at this time.