1. Supplementary slides

2. Mock-ups

3. 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: 61142153 out of 67,213,498 (86%) Transition-transversion ratio: 3.1 # of mutations called: 128,095 Breakdown of exonic mutationsBreakdown of mutations by type:

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

5. ChromosomeCoordinateReferenceAlternativeGenotypedbSNP Exome Variant Server Evolution conservationMutation impactGene Gene description Predicted damageOMIM 1 12345 A T A/T rs123456 A=4564, T=2312 p=0.67 Non-synonymous ACOT4 Acyl-CoA Thioesterase 4 Neutral (0.8) http:// omim.o rg/entr y/6143 14http:// omim.o rg/entr y/6143 14 Full view of the variant table Scroll bar to allow more columns to be shown ChromosomeCoordinateReferenceAlternativedbSNPExome Variant ServerEvolution conservation 1 12345 A T A/T rs123456 A=4564,T=2312 p=0.67 Variant table

6. 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

7. AATCGGATTGATCCCGTAATTGCCTGATACGTGACAGTTGAC SUC23 ChromosomeCoordinateReferenceAlternativedbSNP 10 23454 A C 10 87643 T G rs1364 11 46532 G C 12 2265321 C A 12 7776343 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

8. 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 12 454223 456123 SUC23

9. Focus group instructions Skeleton structure

10. Experiment setup

11. Opening statement

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

13. 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.

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

15. 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?

16. 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?

17. 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?

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

19. 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?

20. 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?

21. 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.

22. 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)

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

24. 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?

25. 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)

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

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

28. 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?

29. 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?

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

31. 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?

32. 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?

33. 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?

34. 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?

35. 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?

36. 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?

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

38. 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)

39. 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?