Supplementary slides. Mock-ups Exome overview Genomic coverage: lower quartile 1, median 23, upper quartile 35 Protocols: Aligner used: BWA v2.3 Reference.

Slides:



Advertisements
Similar presentations
Mapping analysis software Dr Ian Carr PhD. MCSD. Leeds Institute of Molecular Medicine St Jamess University Hospital.
Advertisements

Genetic Approaches to Rare Diseases: What has worked and what may work for AHC Erin L. Heinzen, Pharm.D, Ph.D Center for Human Genome Variation Duke University.
Heredity Overview How are genetic characteristics passed on from one generation to the next?
Genetics SC Biology Standard B The students will be able to predict inherited traits by using the principles of Mendelian Genetics, summarize.
Andrew Novoa and Thea De Guzman 2/1/10 Per. 3
As this disease is most commonly prevalent in the elderly, some members of the class may have relatives with this disease so please be a respectful and.
Theoretical Genetics 4.3 By Anna Samson.
Genetics: Past, Present, and Future Robert M. Fineman, M.D., Ph.D. Web siteWeb site.
Mendel’s Peas and qs: Carla Cáceres, Renée Dawson, Tracey Hickox, Jonathan Marcot, Dick Mueller, Jon Seger, Thayne Sweeten Facilitators: Robin Wright,
Presented by Karen Xu. Introduction Cancer is commonly referred to as the “disease of the genes” Cancer may be favored by genetic predisposition, but.
Autosomal recessive inheritance Risks to children where a parent is affected: the basics a tutorial to show how the genes segregate to give the typical.
Autosomal dominant inheritance Risks to children where both parents are affected: the basics a tutorial to show how the genes segregate to give the typical.
NGS Analysis Using Galaxy
Dr Katie Snape Specialist Registrar in Genetics St Georges Hospital
 What is genetics?  Genetics is the study of heredity, the process in which a parent passes certain genes onto their children. What does that mean?
Whole Exome Sequencing for Variant Discovery and Prioritisation
Standardization of Pedigree Collection. Genetics of Alzheimer’s Disease Alzheimer’s Disease Gene 1 Gene 2 Environmental Factor 1 Environmental Factor.
Question 1___________________________ Question 2___________________________ Question 3 ___________________________ TotalAverage = 44 out of 50 points Important.
Lesson Overview Lesson Overview Human Chromosomes Copyright Pearson Prentice Hall 14–1 Human Chromosomes Chapter 14: Human Heredity.
Next-Generation Sequencing
Allele. Alternate form of a gene gene variant autosome.
Jeopardy Genes and Chromosomes Basics
Genomes and Genomics.
Genetic Testing.
CATALYST Recall and Review: – What are chromosomes? – What are genes? – What are alleles? How do these terms relate to DNA? How do these terms relate to.
Lesson Overview Lesson Overview Human Chromosomes Lesson Overview 14.1 Human Chromosomes.
Next-Generation Sequencing Eric Jorgenson Epidemiology 217 2/28/12.
Linkage analysis Jan Hellemans 6. Finding causal mutations  2 opposing strategies  sequence then select  select then sequence  Sequencing  traditional.
SCRIPPS GENOME ADVISER Galina Erikson Senior Bioinformatics Programmer The Scripps Translational Science Institute Scripps Translational Science Institute.
Chapter 14 - The Human Genome
The Inheritance of Single-Gene Differences
Lesson Overview 14.1 Human Chromosomes.
Human Genome Biology Ch 14.
9 Genes, chromosomes and patterns of inheritance.
Pedigrees Visual Maps for Chromosome Inheritance.
Understanding Genetic Testing
Cell Division.
Lecture 3 Pedigrees and Human Conditions Genes and BioTechnology.
Genetic Diseases and Genetic Counselling Z ? AB C D XY Cl - GHB 2005.
DNA/Genetic Disorder Quiz Review. Any change in a gene or chromosome is a:  Pedigree  Mutation  Karyotype  Genome.
Anjali Sivendra Yanique Bell February 1, 2010 Period 9/10.
Genetic Screening and Counselling
Current Data And Future Analysis Thomas Wieland, Thomas Schwarzmayr and Tim M Strom Helmholtz Zentrum München Institute of Human Genetics Geneva, 16/04/12.
Welcome to the combined BLAST and Genome Browser Tutorial.
Genetic Disorders and Genetic Testing © 2010 Project Lead The Way, Inc.Medical Interventions.
IGCSE BIOLOGY SECTION 3 LESSON 3. Content Section 3 Reproduction and Inheritance a)Reproduction - Flowering plants - Humans b) Inheritance.
14.1 Human Chromosomes Key Questions: 1)What is a karyotype? 2)What patterns of inheritance do human traits follow? 3)How can pedigrees be used to analyze.
How do we interpret the variants?. Overview How do we prioritize the filtered variants? What filters can be used to identify the causative variants? What.
Gene350 Animal Genetics Lecture 5 3 August Last Time Study chromosomes – The normal karyotypes of animals – Chromosomal abnormalities – Chromosomal.
Identifying disease causal variants Mendelian disorders A. Mesut Erzurumluoglu 1.
Reliable Identification of Genomic Variants from RNA-seq Data Robert Piskol, Gokul Ramaswami, Jin Billy Li PRESENTED BY GAYATHRI RAJAN VINEELA GANGALAPUDI.
Lesson Overview Lesson Overview Human Chromosomes Lesson Overview 14.1 Human Chromosomes.
Lesson Overview 14.1 Human Chromosomes. THINK ABOUT IT If you had to pick an ideal organism for the study of genetics, would you choose one that produced.
1 Finding disease genes: A challenge for Medicine, Mathematics and Computer Science Andrew Collins, Professor of Genetic Epidemiology and Bioinformatics.
Interpreting exomes and genomes: a beginner’s guide
Genomic Analysis: GWAS
Disease risk prediction
Interpretation Next Generation Sequencing (Bench Clinic)
Class meetings: TR 3:30-4:50 MCGIL 2315
Content and Labeling of Tests Marketed as Clinical “Whole-Exome Sequencing” Perspectives from a cancer genetics clinician and clinical lab director Allen.
Jeopardy Genes and Chromosomes
AQA GCSE INHERITANCE, VARIATION AND EVOLUTION PART 2
Phevor Combines Multiple Biomedical Ontologies for Accurate Identification of Disease- Causing Alleles in Single Individuals and Small Nuclear Families 
The student is expected to: 6A identify components of DNA, and describe how information for specifying the traits of an organism is carried in the DNA.
Mendelian Inheritance
Unit 5: Heredity Review Lessons 1, 3, 4 & 5.
Pedigrees A Pedigree allows you to trace an inherited (genetic) disease through a family. The pattern of a pedigree helps determine: If the disease is.
Following Patterns of Inheritance in Humans
Analysis of protein-coding genetic variation in 60,706 humans
Inheritance & Variance Traits Vocabulary
Presentation transcript:

Supplementary slides

Mock-ups

Exome overview Genomic coverage: lower quartile 1, median 23, upper quartile 35 Protocols: Aligner used: BWA v2.3 Reference genome version: hg19 Genotype called with: Samtools v.3.5 Data quality: % of reads mapped: out of 67,213,498 (86%) Transition-transversion ratio: 3.1 # of mutations called: 128,095 Breakdown of exonic mutationsBreakdown of mutations by type:

Pedigree construction Assign exome Attach the uploaded exome file to each individual in the pedigree

ChromosomeCoordinateReferenceAlternativeGenotypedbSNP Exome Variant Server Evolution conservationMutation impactGene Gene description Predicted damageOMIM A T A/T rs A=4564, T=2312 p=0.67 Non-synonymous ACOT4 Acyl-CoA Thioesterase 4 Neutral (0.8) omim.o rg/entr y/ http:// omim.o rg/entr y/ Full view of the variant table Scroll bar to allow more columns to be shown ChromosomeCoordinateReferenceAlternativedbSNPExome Variant ServerEvolution conservation A T A/T rs A=4564,T=2312 p=0.67 Variant table

Filters  Mendelian  Custom inheritance filters  List of genes  Frequency  Prediction impact  Mutation type o De novo o Homozygous recessive o Compound heterozygous o Include o Exclude Full view of the variant table SelectChromosomeCoordinateReferenceAlternativedbSNP Exome Variant Server Evolution conservationMutation impactGene Gene description Predicted damage Yes 1 2 Add to candidate list Chromos ome Coordina te Referenc e- alternativ eGene 1 2

AATCGGATTGATCCCGTAATTGCCTGATACGTGACAGTTGAC SUC23 ChromosomeCoordinateReferenceAlternativedbSNP A C T G rs G C C A T G Scroll bar to allow more columns to be shown C/A A/A C/C A A A A A A A A A A A A A A A A

Coverage Analysis Exome Whole genome Exome  All known exons  Specific target regions based on platforms  Custom region All known exons  Specific target regions based on platforms  Custom region  Minimum number of reads ____  Length of uncovered regions ____  Percentage of length uncovered (exon only)____ Minimum number of reads 2 Length of uncovered regions 20 bp Percentage of length uncovered (exon only) 1%. Output Chromosome Coordinate start Coordinate endGene SUC23

Focus group instructions Skeleton structure

Experiment setup

Opening statement

Opening activity In about a minute, please share some recent experiences you have dealing with next- generation sequence data

Imagine you are seeing a patient who is suffering from a not-yet-characterized metabolic disorder. The blood works and clinical symptoms indicate a genetic cause to this presumably rare disorder. You decide to use exome sequencing with a commercial company to try to decipher the genetic cause. When providing the sequence data, the company allows you 2 option: A) to supply you the raw sequenced unaligned DNA reads, or B) the mapped reads with the raw variants called. Please describe which option you would ideally like to work with, or if none of the above.

In your past experience, are there any file formats that you find un-useful or distracting when working with DNA data?

Having decide the type of exome format that you like to work with, now imagine you are supplied with an ideal exome/whole-genome analysis software. How would you like your file to be uploaded to the program? What interface would you like to see?

Imagine you are working with your ideal exome/whole-genome analysis software. You have just uploaded your data to the software. You want to get an overview of the data (ex. any technical abnormalities?) What information would you want to see? How do you want the information to be presented?

Imagine you are now looking at the screen that displays each individual variation and the information attached to each variation (ex. genomic location, mutation type, gene name, allelic frequency, predicted damage). This information is typically presented as a table. Is this what you would like to see in the ideal version as well? Or if not – what other format?

Please describe how you would like to see these information presented on the computer screen

Imagine instead of just working with 1 exome, you now have multiple exomes. These exomes correspond to additional members in the patient’s family, including 2 healthy parents, 1 unaffected sibling, and 1 affected sibling with the same phenotype. Lets assume you want to check the data quality and overall summary of variations (ex. # of variations called in each exome) across this family dataset. How would you want such information to be displayed?

Imagine instead of just working with 1 exome, you now have multiple exomes. These exomes correspond to additional members in the patient’s family, including 2 healthy parents, 1 unaffected sibling, and 1 affected sibling with the same phenotype. One particular variant from the patient exome caught your attention. It is resided in a gene of interest. For that particular variant, what information would you like to see from the family exomes? How would you like it to be displayed?

Based on this family exome data, you want to filter the variants based on the pattern of Mendelian inheritances. Visually, how would you like this function to be carried out – please draw out the interface.

What other types of filtering do you need, beside filtering based upon Mendelian inheritances? (Make a list) If you only have the patient’s exome available and nothing else, what other functions would you employ? (Make a list)

Please draw out how you would like those functionalities to be displayed for user to use.

Often times in a clinical case you have more information about the patient than just the exome (ex. linkage data, regions of homozygosity). What are some other patient data that you would like the system to be able to integrate besides exome to help you narrow your searches? How would you like the system to make use of such data?

Lets assume the variant you were interested in did not work out and there is nothing else that catch your attention. You wonder about the genomic coverage in your dataset. What are the information about genomic coverage that you may wonder about your data? For example, you may wish to know which genes are not sufficiently covered in your exome data. (Make a list)

Draw out how you would want the information to be presented on the computer screen

What information from the exome or whole genome data would you feel is irrelevant or distracting, if any?

Imagine you are using this ideal analysis software to generate a clinical report or sharing findings with collaborators/patients. Are there functionalities that you would like the software to have to facilitate you in this? What about for peer-reviewed publication purposes?

Imagine you are using the software to generate a clinical report or reporting the findings to collaborators, and/or for peer- reviewed publication. Are there functionalities that you would like the software to have to facilitate you in this?

In your past experience, are there any file formats that you find un-useful or distracting when working with DNA data?

Having decide the type of exome format that you like to work with, now imagine you are supplied with an ideal exome/whole-genome analysis software. How would you like your file to be uploaded to the program? What interface would you like to see?

Imagine from the patient exome, you are provided by a bioinformatician a short list of genes and their mutations representing possible impact to the patient’s health, based upon prior literature on the gene, variant frequencies, and mutation type (ex. non-synonymous, frameshift). In the context of genetic counseling, what information would you like to see present on that list to help you decide whether relevant or not to relate to the patient?

In the context of genetic counseling, are there additional databases you would like the software to have access to? What information from the exome or whole genome data would you feel is irrelevant or distracting, if any?

Opening questions What is the name of your profession? (What is the name of your specialty in healthcare?) Have you worked with patient genomic data before? – If yes, how?

Starting stage Scenario: imagine you are seeing this patient who has an undiagnosed genetic disorder. You decide to use exome sequencing to sequence the protein regions for this patient. Do you prefer to work with all the mutations (or variations) seen in the patient DNA? Or do you prefer to work with variants that have already filtered and prioritized variations? (ex. By commercial company) Or anything else?

Variant information Here is an example of a list of mutations seen in a patient. These are the type of information that one can get from the data. Are these information useful? What is lacking?

Variant presentation How would you like the variant list to be presented to you? – Ex: tabular format? – Digital vs. paper copy?

Filtering (For those who like the unfiltered, un-prioritized list): – Types of filters that come across in exome analysis include: Splice site + nonsense > missense > synonymous + intronic De novo heterozygous Compound heterozygous Homozygous recessive X-linked Regions of homozygosity List of genes related to a phenotype Do you see yourself performing those filters if given a user-friendly software? (If yes – briefly describe how that software would look like)

Collaboration In your line of work, do you see yourself having to share the variant data with colleagues? What functionalities can a software have to help you in this manner?