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.

BEAST 1.8.3 / BEAST2 2.4.1 – Bayesian Evolutionary Analysis of Molecular Sequences

BEAST 1.8.3 / BEAST2 2.4.1

:: 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:

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

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

DGEclust 20150607 – Hierarchical non-parametric Bayesian Clustering of Digital Expression data

DGEclust 20150607

:: DESCRIPTION

DGEclust is a program for clustering and differential expression analysis of expression data generated by next-generation sequencing assays, such as RNA-seq, CAGE and others.

::DEVELOPER

Computational Genomics Group, Department of Computer Science, University of Bristol, UK

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 DGEclust 

:: MORE INFORMATION

Citation:

Genome Biol. 2015 Feb 20;16:39. doi: 10.1186/s13059-015-0604-6.
DGEclust: differential expression analysis of clustered count data.
Vavoulis DV, Francescatto M, Heutink P, Gough J.

FreeBayes 1.0.2 – Bayesian Genetic Variant Detector

FreeBayes 1.0.2

:: 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

MrBayes 3.2.5 – Bayesian Inference of Phylogeny

MrBayes 3.2.5

:: 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.

RDP Classifier 2.11 – Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

RDP Classifier 2.11

:: DESCRIPTION

The RDP Classifier is a naive Bayesian classifier that can rapidly and accurately provides taxonomic assignments from domain to genus, with confidence estimates for each assignment

::DEVELOPER

The Ribosomal Database Project 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac OsX /Windows
  • Java

:: DOWNLOAD

 RDP Classifier

:: MORE INFORMATION

Citation

Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.
Wang Q, Garrity GM, Tiedje JM, Cole JR.
Appl Environ Microbiol. 2007 Aug;73(16):5261-7. Epub 2007 Jun 22.

ScreenBEAM 1.0 – Functional Genomics Screens via Bayesian Hierarchical Modeling

ScreenBEAM 1.0

:: DESCRIPTION

ScreenBEAM is an R package to do gene-level meta-anlaysis of high-throughput functional genomics RNAi or CRISPR screening data. Both microarray and NGS data are supported

::DEVELOPER

Jiyang Yu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R

:: DOWNLOAD

 ScreenBEAM

:: MORE INFORMATION

Citation

ScreenBEAM: a Novel Meta-Analysis Algorithm for Functional Genomics Screens via Bayesian Hierarchical Modeling.
Yu J, Silva J, Califano A.
Bioinformatics. 2015 Sep 28. pii: btv556.

BAli-Phy 2.3.7 – Bayesian Alignment and Phylogeny estimation

BAli-Phy 2.3.7

:: DESCRIPTION

BAli-Phy is MCMC software for simultaneous Bayesian estimation of alignment and phylogeny (and other parameters).BAli-Phy can estimate phylogenetic trees from sequence data when the alignment is uncertain. Instead of conditioning on a single alignment estimate, BAli-Phy accounts for alignment uncertainty by integrating over all alignments. BAli-Phy does not rely on a guide tree because the alignment and the tree are co-estimated. Therefore it can construct phylogeny estimates of widely divergent sequences without bias toward a guide tree.

::DEVELOPER

Marc A. Suchard, M.D., Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX / Windows

:: DOWNLOAD

 BAli-Phy

:: MORE INFORMATION

Citation

Suchard MA and Redelings BD
BAli-Phy: simultaneous Bayesian inference of alignment and phylogeny,
Bioinformatics, 22:2047-2048, 2006.

BUCKy 1.4.4 – Gene Tree Reconciliation with Bayesian Concordance Analysis

BUCKy 1.4.4

:: DESCRIPTION

BUCKy (Bayesian Untangling of Concordance Knots) is a free program that implements Bayesian concordance analysis. The method uses a non-parametric clustering of genes with compatible trees, and reconstructs the primary concordance tree from clades supported by the largest proportions of genes. A population tree with branch lengths in coalescent units is estimated from quartet concordance factors. BUCKy estimates the dominant history of sampled individuals, and how much of the genome supports each relationship, using Bayesian concordance analysis. BUCKy does not assume that genes (or loci) all have the same topology. Instead, groups of genes sharing the same tree are detected (while accounting for uncertainty in gene tree estimates), and then combined to gain more resolution on their common tree. No assumption is made regarding the reason for discordance among gene trees.

::DEVELOPER

Cécile Ané Bret Larget

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • C++ Compiler

:: DOWNLOAD

BUCKy

:: MORE INFORMATION

Citation

B. Larget, S.K. Kotha, C.N. Dewey, C. Ané (2010).
BUCKy: Gene tree / species tree reconciliation with the Bayesian concordance analysis.
Bioinformatics (2010) September 21, 2010 doi: 10.1093/bioinformatics/btq539