Searching for interacting QTL Sverker Holmgren, Kajsa Ljungberg, Scientific Computing, UU Örjan Carlborg, Roslin Institute, Scotland Leif Andersson, Animal.

Slides:

Advertisements

Similar presentations

Von Karman Institute for Fluid Dynamics RTO, AVT 167, October, R.A. Van den Braembussche von Karman Institute for Fluid Dynamics Tuning of Optimization.

Advertisements

The genetic dissection of complex traits

Zhiwu Zhang. Complex traits Controlled by multiple genes Influenced by environment Also known as quantitative traits Most traits are continuous, e.g.

Software for Incorporating Marker Data in Genetic Evaluations Kathy Hanford U.S. Meat Animal Research Center Agricultural Research Service U.S. Department.

Introduction Materials and methods SUBJECTS : Balb/cJ and C57BL/6J inbred mouse strains, and inbred fruit fly strains number 11 and 70 from the recombinant.

Chapter 6: Quantitative traits, breeding value and heritability Quantitative traits Phenotypic and genotypic values Breeding value Dominance deviation.

Antibody Response During a PRRS Outbreak can be Predicted Using High-Density SNP Genotypes Nick V.L. Serão 1 *, R.A. Kemp 2, B.E. Mote 3, J.C.S. Harding.

QTL Mapping R. M. Sundaram.

The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL FastANOVA: an Efficient Algorithm for Genome-Wide Association Study Xiang Zhang Fei Zou Wei Wang University.

CISC October Goals for today: Foster’s parallel algorithm design –Partitioning –Task dependency graph Granularity Concurrency Collective communication.

Computer Simulation in Plant Breeding Introduction Outline Application I: Breeding Method Application II: Gene Mapping Application III: Genetic Modeling.

Use of Quantitative Trait Loci (QTL) in Dairy Sire Selection Fabio Monteiro de Rezende Universidade Federal Rural de Pernambuco (UFRPE) - Brazil.

Lecture 5: Learning models using EM

Bull selection based on QTL for specific environments Fabio Monteiro de Rezende Universidade Federal Rural de Pernambuco (UFRPE) - Brazil.

Sequence comparison: Significance of similarity scores Genome 559: Introduction to Statistical and Computational Genomics Prof. James H. Thomas.

Review Session Monday, November 8 Shantz 242 E (the usual place) 5:00-7:00 PM I’ll answer questions on my material, then Chad will answer questions on.

1 Reasons for parallelization Can we make GA faster? One of the most promising choices is to use parallel implementations. The reasons for parallelization.

QTL mapping in animals. It works QTL mapping in animals It works It’s cheap.

ConceptS and Connections

Course on Biostatistics Instructors – Dr. Małgorzata Bogdan Dr. David Ramsey Institute of Mathematics and Computer Science Wrocław University of Technology.

Thursday from QTL to candidate genes Xidan Li Xiaodong Liu DJ de Koning.

Building a Science Base for the Information Age John Hopcroft Cornell University Ithaca, NY Xiamen University.

Genome mapping and sequencing is the core of structural genomics. While no whole genome draft sequences are yet available with aquaculture species, genomes.

Quantitative Genetics. Continuous phenotypic variation within populations- not discrete characters Phenotypic variation due to both genetic and environmental.

Complex Traits Most neurobehavioral traits are complex Multifactorial

Quantitative Genetics

Towards Practical Automated Motion Synthesis Auslander, Fukunaga, Partovi, Christensen, Hsu, Reiss, Shuman, Marks, Ngo.

QTL Mapping in Heterogeneous Stocks Talbot et al, Nature Genetics (1999) 21: Mott et at, PNAS (2000) 97:

 Genetic Algorithms  A class of evolutionary algorithms  Efficiently solves optimization tasks  Potential Applications in many fields  Challenges.

QTL Cartographer A Program Package for finding Quantitative Trait Loci C. J. Basten Z.-B. Zeng and B. S. Weir.

Biologically inspired algorithms BY: Andy Garrett YE Ziyu.

Association between genotype and phenotype

A BRIEF INTRODUCTION TO CACHE LOCALITY YIN WEI DONG 14 SS.

Database Management Systems, R. Ramakrishnan 1 Algorithms for clustering large datasets in arbitrary metric spaces.

Lecture 22: Quantitative Traits II

A Quantitative Overview to Gene Expression Profiling in Animal Genetics Armidale Animal Breeding Summer Course, UNE, Feb Final Remarks Genetical.

GridQTL High Performance QTL analysis via the Grid/Cloud.

Genetic mapping and QTL analysis - JoinMap and QTLNetwork -

MASTITIS RESISTANCE New breeding tools for improving mastitis resistance in European dairy cattle QLK5-CT

The Bovine Genome Sequence: potential resources and practical uses. Nicola Hastings, Andy Law and John L. Williams * * Department of Genetics and Genomics,

HS-LS-3 Apply concepts of statistics and probability to support explanations that organisms with an advantageous heritable trait tend to increase in proportion.

Quantitative analysis of genetic and environmental factors determining variation in cell growth Naomi Ziv, Mark Siegal and David Gresham Center for Genomics.

Bayesian Variable Selection in Semiparametric Regression Modeling with Applications to Genetic Mappping Fei Zou Department of Biostatistics University.

Ø Novel approaches for linkage mapping in dairy cattle

Chicken QTL Phenotype Ontology

Dirk-Jan de Koning*, Örjan Carlborg*, Robert Williams†, Lu Lu†,

Identifying QTLs in experimental crosses

Building a CMMI Data Infrastructure

New Methods for Analyzing Complex Traits

Interval Mapping.

Parallel Programming in C with MPI and OpenMP

Quantitative-Trait Loci Influencing Body-Mass Index Reside on Chromosomes 7 and 13: The National Heart, Lung, and Blood Institute Family Heart Study

The Genetic Basis of Complex Inheritance

Statistical Methods for Quantitative Trait Loci (QTL) Mapping II

Genetic architecture of behaviour

Complex Traits Qualitative traits. Discrete phenotypes with direct Mendelian relationship to genotype. e.g. black or white, tall or short, sick or healthy.

EpiQTL mapping of glucosinolate mean and CV

In these studies, expression levels are viewed as quantitative traits, and gene expression phenotypes are mapped to particular genomic loci by combining.

Quantitative-Trait Loci Influencing Body-Mass Index Reside on Chromosomes 7 and 13: The National Heart, Lung, and Blood Institute Family Heart Study

What are BLUP? and why they are useful?

Meta-analysis of Genetic-Linkage Analysis of Quantitative-Trait Loci

Linkage analysis and genetic mapping

Applications of Genetic Algorithms TJHSST Computer Systems Lab

Volume 377, Issue 9766, Pages (February 2011)

Virtual Memory: Beyond the Physical Memory

William F. Forrest, Eleanor Feingold

Heat map of additive effects for PCs QTL

Modes of selection.

Fig. 1. Summary of linkage analysis and congenic strain

Presentation transcript:

Searching for interacting QTL Sverker Holmgren, Kajsa Ljungberg, Scientific Computing, UU Örjan Carlborg, Roslin Institute, Scotland Leif Andersson, Animal Breeding and Genetics, SLU

Searching for interacting QTL QTL Mapping Quantitative Trait Loci (QTL) = Regions in the genome containing factors influencing a quantitative trait. Goal: Search for several (2-5) interacting QTL Experimental data from several crossings of farm animal available

Searching for interacting QTL QTL Mapping Algorithms Evaluation of test statistics Find global optimum in 2-5 dimensional search space Significance threshold by randomization testing, i.e., perform hundreds of searches on randomized data Earlier algorithms: Searches for 2 interacting QTL demanding New algorithms: Searches for up to at least 5 interacting QTL reasonable

Searching for interacting QTL Computational demands Randomization test embarrassingly parallel, “no” communication Using new algorithm: Each QTL scan requires  A few CPU minutes (2 interacting QTL)  A few CPU days (5 interacting QTL) Main memory requirement 1-2 Gbyte No major demands on secondary storage