Bayesian Evolutionary Analysis by Sampling Trees (BEAST) LEE KIM-SUNG Environmental Health Institute National Environment Agency.

Slides:



Advertisements
Similar presentations
INTRODUCTION TO MACHINE LEARNING Bayesian Estimation.
Advertisements

An Introduction to Phylogenetic Methods
Probabilistic Modeling of Molecular Evolution Using Excel, AgentSheets, and R Jeff Krause (Shodor)
Practical Session: Bayesian evolutionary analysis by sampling trees (BEAST) Rebecca R. Gray, Ph.D. Department of Pathology University of Florida.
Maximum Likelihood. Likelihood The likelihood is the probability of the data given the model.
How missing data and taxon sampling play the role in Phylogeny reconstruction? A case study on a five-gene dataset of Eurotiomycetous endophytic fungi.
Molecular Evolution with an emphasis on substitution rates Gavin JD Smith State Key Laboratory of Emerging Infectious Diseases & Department of Microbiology.
JMeter Workshop Friday 1 December 2006 Anthony Colebourne IT Services The University of Manchester.
Scientific Data Mining: Emerging Developments and Challenges F. Seillier-Moiseiwitsch Bioinformatics Research Center Department of Mathematics and Statistics.
Dispersal models Continuous populations Isolation-by-distance Discrete populations Stepping-stone Island model.
T T07-01 Sample Size Effect – Normal Distribution Purpose Allows the analyst to analyze the effect that sample size has on a sampling distribution.
Probabilistic methods for phylogenetic trees (Part 2)
GENETIC DISTINCTIVENESS OF ITALIAN AUROCHS: NEW INSIGHTS INTO CATTLE DOMESTICATION PROCESS Giulio Catalano (1),Stefano Mona (2), Martina Lari (1), Paolo.
Biology.sdsc.edu CIPRes in Kepler: An integrative workflow package for streamlining phylogenetic data analyses Zhijie Guan 1, Alex Borchers 1, Timothy.
Phylogeny Estimation: Traditional and Bayesian Approaches Molecular Evolution, 2003
Input for the Bayesian Phylogenetic Workflow All Input values could be loaded as text file or typing directly. Only for the multifasta file is advised.
Molecular evidence for endosymbiosis Perform blastp to investigate sequence similarity among domains of life Found yeast nuclear genes exhibit more sequence.
Phylogenetic Analysis Dayong Guo. Introduction Phylogenetics is the study of evolutionary relatedness among various species, populations, or among a set.
Characterization of antigenetic serotypes from the dengue virus in Venezuela by means of Grid Computing R. Isea 1, E. Montes 2, A.J. Rubio-Montero 2, J.D.
UPPMAX and UPPNEX: Enabling high performance bioinformatics Ola Spjuth, UPPMAX
Phylogenetic Analysis. General comments on phylogenetics Phylogenetics is the branch of biology that deals with evolutionary relatedness Uses some measure.
Lecture 25 - Phylogeny Based on Chapter 23 - Molecular Evolution Copyright © 2010 Pearson Education Inc.
Algoval: Evaluation Server Past, Present and Future Simon Lucas Computer Science Dept Essex University 25 January, 2002.
The use of short-read next generation sequences to recover the evolutionary histories in multi-individual samples Systematic biology presentation Yuantong.
PAML: Phylogenetic Analysis by Maximum Likelihood Ziheng Yang Depart of Biology University College London
Molecular phylogenetics 4 Level 3 Molecular Evolution and Bioinformatics Jim Provan Page and Holmes: Sections
March 26, 2007 Phyloinformatics of Neuraminidase at Micro and Macro Levels using Grid-enabled HPC Technologies B. Schmidt (UNSW) D.T. Singh (Genvea Biosciences)
Biological inferences from barcoding data Timothy G. Barraclough Establishing a standard DNA barcode for land plants.
DNA Barcoding Statistics Rasmus Nielsen University of Copenhagen.
Chapter 8 Molecular Phylogenetics: Measuring Evolution.
MOLECULAR PHYLOGENETICS Four main families of molecular phylogenetic methods :  Parsimony  Distance methods  Maximum likelihood methods  Bayesian methods.
Grid enabling phylogenetic inference on virus sequences using BEAST - a possibility? EUAsiaGrid Workshop 4-6 May 2010 Chanditha Hapuarachchi Environmental.
Calculating branch lengths from distances. ABC A B C----- a b c.
How to date Xuhua Xia
More statistical stuff CS 394C Feb 6, Today Review of material from Jan 31 Calculating pattern probabilities Why maximum parsimony and UPGMA are.
Patterns of divergent selection from combined DNA barcode and phenotypic data Tim Barraclough, Imperial College London.
PhyloGrid: a development for a workflow in Phylogeny E. Montes 1, R. Isea 2 and R. Mayo 1 1 CIEMAT, Avda. Complutense, 22, Madrid, Spain 2 Fundación.
Coalescent Models for Genetic Demography
Rooting Phylogenetic Trees with Non-reversible Substitution Models Von Bing Yap* and Terry Speed § *Statistics and Applied Probability, National University.
David Adams ATLAS DIAL: Distributed Interactive Analysis of Large datasets David Adams BNL August 5, 2002 BNL OMEGA talk.
SAN DIEGO SUPERCOMPUTER CENTER at the UNIVERSITY OF CALIFORNIA, SAN DIEGO Hybrid MPI/Pthreads Parallelization of the RAxML Phylogenetics Code Wayne Pfeiffer.
Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise.
Clustering and Geography: Analysis of HIV Transmission among UK MSM Lucy Weinert* 1, Gareth Hughes 1, Esther Fearnhill 2, David Dunn 2, Andrew Rambaut.
By Mireya Diaz Department of Epidemiology and Biostatistics for EECS 458.
Recent Enhancements to Quality Assurance and Case Management within the Emissions Modeling Framework Alison Eyth, R. Partheepan, Q. He Carolina Environmental.
Automatic and manual sequence alignment Inferring phylogenetic trees Mining web-based databases Estimating rates of molecular evolution Testing evolutionary.
Bayesian statistics named after the Reverend Mr Bayes based on the concept that you can estimate the statistical properties of a system after measuting.
Bioinf.cs.auckland.ac.nz Juin 2008 Uncorrelated and Autocorrelated relaxed phylogenetics Michaël Defoin-Platel and Alexei Drummond.
1 ParadisEO-MOEO for a Bi-objective Flow-Shop Scheduling Problem May 2007 E.-G. Talbi and the ParadisEO team
Bayesian Hierarchical Clustering Paper by K. Heller and Z. Ghahramani ICML 2005 Presented by David Williams Paper Discussion Group ( )
Species Tree Workshop January 14, 2012 Practice with BEST Please download MrBayes 3.2 for either Windows, Macintos, or UNIX from
HW7: Evolutionarily conserved segments ENCODE region 009 (beta-globin locus) Multiple alignment of human, dog, and mouse 2 states: neutral (fast-evolving),
Full modeling versus summarizing gene- tree uncertainty: Method choice and species-tree accuracy L.L. Knowles et al., Molecular Phylogenetics and Evolution.
Scaling bio-analyses from computational clusters to grids George Byelas University Medical Centre Groningen, the Netherlands IWSG-2013, Zürich, Switzerland,
Jump to first page Bayesian Approach FOR MIXED MODEL Bioep740 Final Paper Presentation By Qiang Ling.
Konstantin Okonechnikov Qualimap v2: advanced quality control of
Workshop Biogeography
Associate Professor Daniel Wilson
BEAUTY AND THE BEAST МАРТ 2010 г..
Workshop on data analyses
Statistical Modeling of Ancestral Processes
Molecular Clocks Rose Hoberman.
Sampling Distribution
Sampling Distribution
the goal of Bayesian divergence time estimation
Enrique Garcia-Assad, Indresh Singh, Pratap Venepally, Jason Inman
Morphological Phylogenetics in the Genomic Age
Tracing the Evolution of Hepatitis C Virus in the United States, Japan, and Egypt By Using the Molecular Clock  Masashi Mizokami, Yasuhito Tanaka  Clinical.
Statistical Process Control
Statistical Process Control
Presentation transcript:

Bayesian Evolutionary Analysis by Sampling Trees (BEAST) LEE KIM-SUNG Environmental Health Institute National Environment Agency

Analysis of Sequence Variation Polymorphisms Phylogenetics Statistic and evolution  Parameter estimation  Hypothesis testing

BEAST Framework for parameter estimation and hypothesis testing of evolutionary models Bayesian statistical framework  Combination of prior knowledge and data information Cross-platform for Bayesian MCMC analysis of molecular sequences

BEAST Drummond AJ, Rambaut A (2007) "BEAST: Bayesian evolutionary analysis by sampling trees." BMC Evolutionary Biology 7: versions since June 2003  Increasing range of models implemented >150 publications Java platform Open source

What can BEAST do? Molecular clock models  constant, variable (relaxed)  Non-contemporaneous sequences (tipdate)  Local clock Coalescent models  Population size and growth  Multi-locus Estimation of divergence date Substitution model heterogeneity across sites Flexible model specification

BEAST Workflow Sequence alignment Generating XML in Beauti Running BEAST Specify parameters and models Analyzing BEAST output Tracer Tree Annotater Low ESS

Beauti : Generating XML file A graphical user interface for generating BEAST XML input files for a number of model combinations

Running BEAST

Tracer: Analyzing BEAST output

Phylogenetic Analysis

Demographic history

Grid Enabled BEAST? BEAST performance   dictated by speed of likelihood evaluation at each state   dataset,  parameter   running time  e.g. Phylogeographic analysis   11 days (Core 2 Duo, 2.8 GHz, 4GB RAM)   5 days (Mac Cluster) Possibility of Grid computing for BEAST?

Thank You