Polygenic scores (PGS) aggregate the effects of hundreds-to-millions of variants across the genome into a single score and have been shown to have predictive value for many common diseases and traits. PGS are actively being translated into the clinic; however there is no central resource available for this data. To address this we are developing a PGS Catalog (www.pgscatalog.org) to collect and disseminate the information necessary to support uses of PGS.

To ensure the PGS Catalog meets the needs of the community we would like to find out a bit about you, how you might use the Catalog and what types of information you would most like included.

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* 1. Which of the following categories best describe your current position?

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* 2. What is you research interest or area of expertise?

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* 3. Would an open database of previously developed PGS (like the PGS Catalog) be useful to you in your work?

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* 4. How would you use a PGS Catalog in your work?

The following questions relate to the data we extract and display for each PGS. You may wish to refer to an example PGS (http://www.pgscatalog.org/pgs/PGS000018) for Coronary Artery Disease which has a representative set of annotations.

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* 5. Please rate how useful you would find the following types of information relating to a polygenic score. (Current PGS fields are labeled in brackets)

  Not at all helpful Not so helpful Somewhat helpful Very helpful Extremely helpful
The trait predicted by the PGS (Reported Trait)
Ontology trait representation (Mapped Trait(s))
A name for each PGS, usually given by the PGS’ developers (Score Name)
The computational method used to develop the PGS (PGS Development Method)
The parameters and settings used by the PGS training method (PGS Development Details/Relevant Parameters)
The reported performance metrics

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* 6. Please rate how useful you would find the following types of information relating to the samples used to train and evaluate a PGS. (Current PGS fields are labeled in brackets)

  Not at all helpful Not so helpful Somewhat helpful Very helpful Extremely helpful
References to the source of the samples e.g. PubMed IDs, GWAS Catalog Study Accessions (Study Identifiers)
The number of individuals in each study (Sample Numbers)
The sex of the samples (% Male Samples)
The ancestries of the samples (Sample ancestry and Additional Ancestry Description)
A detailed trait description (e.g. ICD/SNOMED codes used to identify cases) for each set of samples (Detailed Phenotype Description)
The name of the cohort that the samples originated from (Cohort(s))

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* 7. Please rate how useful you would find the following types of information relating to the performance metrics extracted for each PGS.

  Not at all helpful Not so helpful Somewhat helpful Very helpful Extremely helpful
Effect sizes (e.g. Beta, Odds Ratio [OR], Hazard Ratio [HR]) per one standard deviation (SD) change in PGS
Metrics of classification accuracy (e.g. Area Under the Receiver Operating Characteristic Curve [AUROC], Concordance statistic [C-index])
Other performance metrics that do not fall into the above two categories
Covariates that were used to estimate the PGS performance

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* 8. What key information about PGS performance is necessary for the use of the scores?

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* 9. How would you want to access data?

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* 10. Is there any information missing from the current PGS Catalog that you would like included?

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* 11. Please provide any additional comments on the PGS Catalog

Thank you for helping us to improve the PGS Catalog!
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