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ipPCA

iterative pruning Principal Component Analysis

i2ppca_logo.png  i2pPCA (Version 2)  

The i2pPCA software is developed on the original ipPCA framework including additional functions that result in improved population assignment accuracy. This has been achieved through several new features:

1) Universal genotype data encoding scheme which allows the population analysis of all types of genetic markers; Single Nucleotide Polymorphism (SNP), Short Tandem Repeat (STR) and RFLP.

2) New termination criterion called “EigenDev” which is more robust to population sampling, thus provides the better estimation of number of assigned subpopulations (K) and higher accuracy for the analysis of large complex population datasets.

 

Download software

 

Download input files and python scripts

    (Binary allelic encoding of Xing et. al. 's SNPs input file)

    (Binary allelic encoding of Tishkoff et. al. 's microsatellite input file)

i2pPCA Results

 


 

ipPCA (Version 1)

 

Download software click here

  • ipPCA Matlab executable for Linux x86_64 system (ipPCAgui-linx86-64.zip)
  • ipPCA Matlab executable for Windows 32 (ipPCAgui_pkg.exe)
  • ipPCA source code (M file, ipPCAsoftware.zip)

 

Download input files in CSV format (Right-click, Save Target As...)

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ipPCA Results

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Additional Results on PCA and iteration-zero k-mean clustering using k = labels

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