piMASS 0.9 – Posterior Inference via Model Averaging & Subset Selection

piMASS 0.9

:: DESCRIPTION

piMASS (Posterior inference using Model Averaging and Subset Selection) performs multi-SNP association with disease phenotypes. It can handle all SNPs in the genome simultaneously.piMASS was developed to perform multi-SNP association analysis for large (genome-wide) datasets, although it can also be applied to smaller association analysis data (e.g. candidate genes or regions), and in this case it forms an alternative to the multi-SNP association analysis capabilities of BIMBAM (below). It may also be useful for Bayesian variable selection regression in large-scale problems more generally.

::DEVELOPER

Yongtao Guan

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac

:: DOWNLOAD

 piMASS

:: MORE INFORMATION

Citation

Ann. Appl. Stat. Volume 5, Number 3 (2011), 1780-1815.
Bayesian variable selection regression for genome-wide association studies and other large-scale problems
Yongtao Guan and Matthew Stephens

Kaks_Calculator 2.0 – Calculate Ka and Ks through Model Selection and Model Averaging

Kaks_Calculator 2.0

:: DESCRIPTION

KaKs_Calculator adopts model selection and model averaging to calculate nonsynonymous (Ka) and synonymous (Ks) substitution rates, attempting to include as many features as needed for accurately capturing evolutionary information in protein-coding sequences. In addition, several existing methods for calculating Ka and Ks are also incorporated into KaKs_Calculator.

::DEVELOPER

The National Genomics Data Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows

:: DOWNLOAD

 KaKs_Calculator

:: MORE INFORMATION

Citation:

Genomics Proteomics Bioinformatics. 2010 Mar;8(1):77-80. doi: 10.1016/S1672-0229(10)60008-3.
KaKs_Calculator 2.0: a toolkit incorporating gamma-series methods and sliding window strategies.
Wang D1, Zhang Y, Zhang Z, Zhu J, Yu J.

Zhang Zhang, Jun Li,Xiao-QianZhao,etal.
KaKs_Calculator: calculating Ka and Ks through model selection and model averaging
Geno. Prot. Bioinfo.,2006,4(4)

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