MSBayesPro – Bayesian Protein Inference for LC-MS/MS Proteomics experiment

MSBayesPro

:: DESCRIPTION

MSBayesPro is a software package and web tool for Bayesian protein inference from tandem mass spectrometry peptide identifications. It uses a set of identified peptides (or peptides with scores in a MS/MS search), peptide detectability, and a protein database to provide probabilities of protein identifications.

::DEVELOPER

Yong Fuga Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows

:: DOWNLOAD

 MSBayesPro

:: MORE INFORMATION

Citation

J Comput Biol. 2009 Aug;16(8):1183-93. doi: 10.1089/cmb.2009.0018.
A bayesian approach to protein inference problem in shotgun proteomics.
Li YF1, Arnold RJ, Li Y, Radivojac P, Sheng Q, Tang H.

FreeBayes 1.3.1 – Bayesian Genetic Variant Detector

FreeBayes 1.3.1

:: DESCRIPTION

FreeBayes is a high-performance, flexible, and open-source Bayesian genetic variant detector. It operates on BAM alignment files, which are produced by most contemporary short-read aligners.

::DEVELOPER

The MarthLab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  FreeBayes

:: MORE INFORMATION

Citation

Haplotype-based variant detection from short-read sequencing
Erik Garrison, Gabor Marth

BEAST 1.10.4 / BEAST2 2.6.1 – Bayesian Evolutionary Analysis of Molecular Sequences

BEAST 1.10.4 / BEAST2 2.6.1

:: DESCRIPTION

BEAST (Bayesian Evolutionary Analysis Samling Trees) is a cross-platform program for Bayesian MCMC analysis of molecular sequences. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. We include a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.

BEAST 2 is an open source cross-platform program for Bayesian MCMC phylogenetic analysis of molecular sequences.

::DEVELOPER

The University of Auckland Computational Evolution Group

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • Java

:: DOWNLOAD

BEAST /BEAST2

:: MORE INFORMATION

Citation:

BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.
Bouckaert R, Vaughan TG, Barido-Sottani J, Duchêne S, Fourment M, Gavryushkina A, Heled J, Jones G, Kühnert D, De Maio N, Matschiner M, Mendes FK, Müller NF, Ogilvie HA, du Plessis L, Popinga A, Rambaut A, Rasmussen D, Siveroni I, Suchard MA, Wu CH, Xie D, Zhang C, Stadler T, Drummond AJ.
PLoS Comput Biol. 2019 Apr 8;15(4):e1006650. doi: 10.1371/journal.pcbi.1006650.

Bayesian inference of sampled ancestor trees for epidemiology and fossil calibration.
Gavryushkina A, Welch D, Stadler T, Drummond AJ.
PLoS Comput Biol. 2014 Dec 4;10(12):e1003919. doi: 10.1371/journal.pcbi.1003919.

Alexei J Drummond and Andrew Rambaut
BEAST: Bayesian evolutionary analysis by sampling trees
BMC Evolutionary Biology 2007, 7:214doi:10.1186/1471-2148-7-214

Tracer 1.7.1 – Analyse Results from Bayesian MCMC programs such as BEAST & MrBayes

Tracer 1.7.1

:: DESCRIPTION

Tracer is a program for analysing the trace files generated by Bayesian MCMC runs (that is, the continuous parameter values sampled from the chain). It can be used to analyse runs of BEAST, MrBayes, LAMARC and possibly other MCMC programs.

::DEVELOPER

Andrew Rambaut Group

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • Java

:: DOWNLOAD

Tracer

:: MORE INFORMATION

Citation

Syst Biol. 2018 Sep 1;67(5):901-904. doi: 10.1093/sysbio/syy032.
Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7.
Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA.

MrBayes 3.2.7a – Bayesian Inference of Phylogeny

MrBayes 3.2.7a

:: DESCRIPTION

MrBayes is a program for the Bayesian estimation of phylogeny. Bayesian inference of phylogeny is based upon a quantity called the posterior probability distribution of trees, which is the probability of a tree conditioned on the observations. The conditioning is accomplished using Bayes’s theorem. The posterior probability distribution of trees is impossible to calculate analytically; instead, MrBayes uses a simulation technique called Markov chain Monte Carlo (or MCMC) to approximate the posterior probabilities of trees.

::DEVELOPER

MrBayes Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / MacOsX / Linux

:: DOWNLOAD

MrBayes

:: MORE INFORMATION

Citation:

MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space.
Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, Larget B, Liu L, Suchard MA, Huelsenbeck JP.
Syst Biol. 2012 May;61(3):539-42. doi: 10.1093/sysbio/sys029.

Ronquist F, Huelsenbeck JP.
MrBayes 3: Bayesian phylogenetic inference under mixed models.
Bioinformatics. 2003 Aug 12;19(12):1572-4.

ExaBayes 1.5 – Parallelized Bayesian Tree Inference for large-scale datasets

ExaBayes 1.5

:: DESCRIPTION

ExaBayes is a software package for Bayesian tree inference. It is particularly suitable for large-scale analyses on computer clusters.

::DEVELOPER

the Exelixis Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOs

:: DOWNLOAD

ExaBayes

:: MORE INFORMATION

Citation

ExaBayes: massively parallel bayesian tree inference for the whole-genome era.
Aberer AJ, Kobert K, Stamatakis A.
Mol Biol Evol. 2014 Oct;31(10):2553-6. doi: 10.1093/molbev/msu236

ABCRF 1.8 – Approximate Bayesian Computation via Random Forests

ABCRF 1.8

:: DESCRIPTION

ABCRF is an R library to perform Approximate Bayesian Computation (ABC) model choice and parameter inference via random forests.

::DEVELOPER

The Computational Biology Institute (IBC)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux /macOsX
  • R

:: DOWNLOAD

ABCRF

:: MORE INFORMATION

Citation

Bioinformatics. 2019 May 15;35(10):1720-1728. doi: 10.1093/bioinformatics/bty867.
ABC random forests for Bayesian parameter inference.
Raynal L, Marin JM, Pudlo P, Ribatet M, Robert CP, Estoup A

Bayesian Joint Analysis

Bayesian Joint Analysis

:: DESCRIPTION

Bayesian Joint Analysis is an approach to address the two key questions in parallel, which incorporates the information of functional annotations into expression data analysis and meanwhile infer the enrichment of functional groups.

::DEVELOPER

The Quantitative Biomedical Research Center 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R

:: DOWNLOAD

 Bayesian Joint Analysis 

:: MORE INFORMATION

Citation

Wang X, Chen M, Khodursky AB and Xiao G,
Bayesian Joint Analysis of Gene Expression Data and Gene Functional Annotations,
Statistics in Biosciences. 2012 Nov; 4(2): 300-318

HaMMLET – Fast Bayesian Hidden Markov Model with Wavelet Compression

HaMMLET

:: DESCRIPTION

HaMMLET is a fast Forward-Backward Gibbs sampler for Bayesian inference on Hidden Markov Models (HMM). It uses the Haar wavelet transform to dynamically compress the data based on the current variance sample in each iteration.

::DEVELOPER

Schliep lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • GCC

:: DOWNLOAD

 HaMMLET

:: MORE INFORMATION

Citation

Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression.
Wiedenhoeft J, Brugel E, Schliep A.
PLoS Comput Biol. 2016 May 13;12(5):e1004871. doi: 10.1371/journal.pcbi.1004871.

bam2mpg 1.0.1 – Bayesian Genotype Caller for NextGen Sequencing Data

bam2mpg 1.0.1

:: DESCRIPTION

bam2mpg calls genotypes from sequence reads of haploid or diploid DNA aligned to a closely-related reference sequence. The program reads alignments in BAM format (http://samtools.sourceforge.net). The MPG (Most Probable Genotype) algorithm is based on a Bayesian model which simulates sampling from one or two alleles with sequencing error, and then calculates the likelihood of each possible genotype given the observed sequence data. Using prior probabilities dependent on the expected heterozygosity of the sequence, MPG then predicts the “Most Probable Genotype” at each site, along with quality scores estimating the accuracy of the calls.

::DEVELOPER

bam2mpg Team  @ NHGRI

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 bam2mpg

:: MORE INFORMATION