Using Familias and FamLink Athens 29 May, 2014. Familias 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES.

Slides:



Advertisements
Similar presentations
Forensic DNA Inference ICFIS 2008 Lausanne, Switzerland Mark W Perlin, PhD, MD, PhD Joseph B Kadane, PhD Robin W Cotton, PhD Cybergenetics ©
Advertisements

Attaching statistical weight to DNA test results 1.Single source samples 2.Relatives 3.Substructure 4.Error rates 5.Mixtures/allelic drop out 6.Database.
Statistical methods for genetic association studies
Introduction to Monte Carlo Markov chain (MCMC) methods
How TrueAllele ® Works (Part 3) Kinship, Paternity and Missing Persons Cybergenetics Webinar December, 2014 Mark W Perlin, PhD, MD, PhD Cybergenetics,
Forensics and DNA Statistics Harry R Erwin, PhD CIS308 Faculty of Applied Sciences University of Sunderland.
1 Statistical genetics and genetical statistics Thore Egeland, Rikshospitalet and Section of Medical Statistics Joint work with P. Mostad, NR, B. Olaisen,
1 Familias Thore Egeland, Rikshospitalet and Section of Medical Statistics Joint work with P. Mostad, NR, B. Olaisen, B. Mevåg, M. Stenersen, Inst of Forensic.
METHODS FOR HAPLOTYPE RECONSTRUCTION
Tutorial #5 by Ma’ayan Fishelson. Input Format of Superlink There are 2 input files: –The locus file describes the loci being analyzed and parameters.
Basics of Linkage Analysis
Workshop Biostatistics in relationship testing ESWG-meeting 2014 Daniel Kling Norwegian Institute of Public Health and Norwegian University of Life Sciences,
Joint Linkage and Linkage Disequilibrium Mapping
Fundamentals of Forensic DNA Typing Slides prepared by John M. Butler June 2009 Appendix 3 Probability and Statistics.
ISSPIT Ajman University of Science & Technology, UAE
Ronnie A. Sebro Haplotype reconstruction BMI /21/2004.
Representing and Solving Complex DNA Identification Cases Using Bayesian Networks Philip Dawid University College London Julia Mortera & Paola Vicard Università.
DATA ANALYSIS Module Code: CA660 Lecture Block 2.
IGES 2003 How many markers are necessary to infer correct familial relationships in follow-up studies? Silvano Presciuttini 1,3, Chiara Toni 2, Fabio Marroni.
Introduction to Linkage Analysis March Stages of Genetic Mapping Are there genes influencing this trait? Epidemiological studies Where are those.
Efficient Estimation of Emission Probabilities in profile HMM By Virpi Ahola et al Reviewed By Alok Datar.
Genotyping of James Watson’s genome from Low-coverage Sequencing Data Sanjiv Dinakar and Yözen Hernández.
Inferring Haplotypes Dr. Russell Thomson. A Haplotype. …AGCTATATTA…..GGCTGCTC…..AGCAGCGA… …AGCTAAATTA…..GGCTCCTC…..AGCAGCGA… One individual. Marker 1Marker.
Kernel Methods Part 2 Bing Han June 26, Local Likelihood Logistic Regression.
Assigning individuals to ethnic groups based on 13 STR loci X. Fosella 1, F. Marroni 1, S. Manzoni 2, A. Verzeletti 2, F. De Ferrari 2, N. Cerri 2, S.
Tutorial #5 by Ma’ayan Fishelson Changes made by Anna Tzemach.
General Explanation There are 2 input files –The locus file describes the loci being analyzed and parameters for the different analyzing programs. –The.
Linkage Analysis in Merlin
New Technologies Y-STR DNA Pedigree (7 generations)
Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.
Family Tree Maker 2006 Unlocking Its Mysteries. Getting Started.
Software Breakdown. Monday, October 26, 2009 CS410 Green Team Fall High Level Architecture.
Calculation of IBD State Probabilities Gonçalo Abecasis University of Michigan.
Comp. Genomics Recitation 3 The statistics of database searching.
SCHOOL ADMINISTRATION SYSTEM Designed specially for an educational institution to manage their pupils’ general bio data.
HMMs for alignments & Sequence pattern discovery I519 Introduction to Bioinformatics.
Permutation Analysis Benjamin Neale, Michael Neale, Manuel Ferreira.
Lecture 13: Linkage Analysis VI Date: 10/08/02  Complex models  Pedigrees  Elston-Stewart Algorithm  Lander-Green Algorithm.
Lecture 15: Linkage Analysis VII
Physics Exercise Generation and Simulation Interface Welcome! Login as Student Login as Instructor Register as Instructor Register as Student.
Cybergenetics Webinar January, 2015 Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA Cybergenetics © How TrueAllele ® Works (Part 4)
Class Scheduler Team Members Bernard Battle Jerad Blake James Knoch Chris Louallen Lenora Pride.
Getting Past First Bayes with DNA Mixtures American Academy of Forensic Sciences February, 2014 Seattle, WA Mark W Perlin, PhD, MD, PhD Cybergenetics,
Implications of database searches for DNA profiling statistics Forensic Bioinformatics ( Dan E. Krane, Wright State University, Dayton,
Errors in Genetic Data Gonçalo Abecasis. Errors in Genetic Data Pedigree Errors Genotyping Errors Phenotyping Errors.
Practical With Merlin Gonçalo Abecasis. MERLIN Website Reference FAQ Source.
Lecture 15: Individual Identity and Paternity Analysis
PCR Y.Martinez, LSHS, 2014 DIRECTIONS: COPY NOTES IN ORANGE.
Chapter 23: Evaluation of the Strength of Forensic DNA Profiling Results.
Individual Identity and Population Assignment Lab. 8 Date: 10/17/2012.
Anders Nielsen Technical University of Denmark, DTU-Aqua Mark Maunder Inter-American Tropical Tuna Commission An Introduction.
Lecture 16: Paternity Analysis and Phylogenetics October 19, 2012.
Mendel & Genetic Variation Chapter 14. What you need to know! The importance of crossing over, independent assortment, and random fertilization to increasing.
Seventh Annual Prescriptions for Criminal Justice Forensics Program Fordham University School of Law June 3, 2016 DNA Panel.
Genetic Algorithm(GA)
Introduction We consider the data of ~1800 phenotype measurements Each mouse has a given probability distribution of descending from one of 8 possible.
Regression Models for Linkage: Merlin Regress
Gonçalo Abecasis and Janis Wigginton University of Michigan, Ann Arbor
ESWG paper challenges – A walkthrough Athen, May 29, 2014
Regression-based linkage analysis
JS 115 Validation Pre class activities Database issues- Continued
Error Checking for Linkage Analyses
Investigative DNA Databases that Preserve Identification Information
Familias and Forensic genetics Thore.
2018 AAFS Annual Scientific Meeting February 22, 2018
A Flexible Bayesian Framework for Modeling Haplotype Association with Disease, Allowing for Dominance Effects of the Underlying Causative Variants  Andrew.
IBD Estimation in Pedigrees
Accounting for linkage between the STR loci D5S818/CSF1PO and vWA/D12S391 in kinship analyses: Impact on likelihood ratio values  H. Burri, A. Sulzer,
X-chromosomal markers and FamLinkX
Gonçalo R. Abecasis, Janis E. Wigginton 
Presentation transcript:

Using Familias and FamLink Athens 29 May, 2014

Familias 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Familias 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES – Calculate likelihoods in relationship testing – Define “arbitrary” relationships – Different mutation models – Silent alleles – Subpopulation correction – Generate pedigrees – Calculate priors – Easy to use / Userfriendly

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Define general frequency database -Change mutations

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Define marker specific database sizes -Define dropout probability -Mutations -Silent allele

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Case data dialog -Import/Edit DNA data -Compare profiles

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Compare profiles

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Random match probability

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Define pedigrees/hypotheses

Familias – At a glance 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Defining relations -As Parent-Child Paternity: Siblings: ParentChild Alleged fatherChild MotherChild ParentChild FatherSibling1 MotherSibling1 FatherSibling2 MotherSibling2

Recent news in Familias 3 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES – New mutation model – Simulation interface – DVI module – Blind search feature – Direct matching – Random match calculation – Create database feature – Dropouts

Familias – Simulations 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Simulation options

Familias – Simulations 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Simulation results

Familias – Simulations 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Simulations -Find good thresholds -False positive/negative rate -Investigate what we can expect -Include -Kinship -Mutations -Silent alleles -Multiple pedigrees -Investigate the number of persons we must genotype -Investigate the number of markers we must include

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -What is a DVI operation? -What is the purpose of developing a DVI module? -“Alternative” softwares -Brief overview -Blind search module

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Add Unidentified persons

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Blind search

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Blind search results

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Add reference data

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Edit reference family

Familias – DVI 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -Matching

Familias – Dropouts 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES -What is a dropout? -The model -Conditional genotype probabilities -Dropout probability -Low quality profiles -Estimation of dropout probabilities -Logistic regression -LR for a number of dropout probabilities

Dropout versus silent allele 23 L1: 16,17 L2: 10,11 L1: 17,18 L2: 10,10 L1: 19,19 L2: 12,12

Familias–Questions? 30 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink  What can FamLink do? –––––– User-friendly software Similar to Familias in many ways Perform likelihood calculations on a number of pedigrees Takes linkage between markers into account Does not implement a good mutation model Simulation interface predefined –––––––– Implements the Lander-Green Different than Familias Merlin algorithm 10 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –Defineallelefrequencydatabase –Currently restricted to two markers 11 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –Definerecombinationrate –Between 0 and w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –Convertgeneticdistance(cM)(cM)torecombinationrate 13 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –Selectmainhypothesis 14 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –Selectalternativehypotheses 15 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –DefineDNADNAdata 16 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – At a glance –Calculatelikelihoods –We display two methods 17 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink – Familias connection –Calculate likelihoods for aFamiliasproject –Get likelihoods for all your markers LinkageLinkageconsideredfor all markers 18 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

FamLink–Questions? 30 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES

EXERCISES 31 w w.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES