SIBIS 1.0 – Bayesian model for Inconsistent Protein Sequence Estimation

SIBIS 1.0

:: DESCRIPTION

SIBIS (Bayesian Inconsistency in Sequences) is designed to detect such inconsistencies based on the evolutionary information in multiple sequence alignments. A Bayesian framework, combined with Dirichlet mixture models, is used to estimate the probability of observing specific amino acids and to detect inconsistent or erroneous sequence segments.

::DEVELOPER

Julie Dawn Thompson

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 SIBIS

:: MORE INFORMATION

Citation

Bioinformatics. 2014 May 13. pii: btu329. [Epub ahead of print]
SIBIS: A Bayesian model for inconsistent protein sequence estimation.
Khenoussi W1, Vanhoutrève R1, Poch O1, Thompson JD2.

BaDGE 1.1.7 – Bayesian model for Detecting Gene Environment interaction

BaDGE 1.1.7

:: DESCRIPTION

BaDGE is a R package implementing the Bayeisan model for detecting gene environment interaction

::DEVELOPER

 DCEG

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package

:: DOWNLOAD

 BaDGE

:: MORE INFORMATION

Citation

Yu K , Wacholder S , Wheeler W , Wang Z , Caporaso N , et al. 2012
A Flexible Bayesian Model for Studying Gene–Environment Interaction.
PLoS Genet 8(1): e1002482.

RVD 27 – Hierarchical Bayesian model to detect Rare Single Nucleotide Variants

RVD 27

:: DESCRIPTION

RVD2 is an ultra-sensitive variant detection model for low-depth targeted next-generation sequencing data

::DEVELOPER

Flaherty Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux
  • Python

:: DOWNLOAD

 RVD2

:: MORE INFORMATION

Citation

RVD2: An ultra-sensitive variant detection model for low-depth heterogeneous next-generation sequencing data.
He Y, Zhang F, Flaherty P.
Bioinformatics. 2015 Apr 29. pii: btv275.

MCMC++ 1.2 – C++ class library for Monte Carlo Markov Chain Analysis of Bayesian models

MCMC++ 1.2

:: DESCRIPTION

MCMC++ is a class library intended to speed and simplify development of Markov Chain Monte Carlo models for analysis of data in a Bayesian context.

::DEVELOPER

Kent Holsinger

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • C++ Compiler

:: DOWNLOAD

 MCMC++

:: MORE INFORMATION