In maialab/quincunx: REST API Client for the 'PGS' Catalog

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PGS performance metrics

Performance metrics assess the validity of a PGS in a Sample Set. This assessment is performed on samples not used for score development.

Performance metrics are retrieved with the function get_performance_metrics(). The returned data is provided as an S4 object of class performance_metrics.

Common metrics include:

• standardized effect sizes: odds ratios or hazard ratios, and regression coefficients $\beta$, see slot pgs_effect_sizes;
• classification accuracy metrics: area under the receiver operating characteristic curve, C-index and area under the precision-recall curve, see slot pgs_classification_metrics;
• other relevant metrics: calibration ($\chi^2$)), see slot pgs_other_metrics.

The covariates used in the model (most commonly age, sex and genetic principal components to account for the population structure) are also recorded for each set of metrics. These can be found in the slot demographics.

Getting PGS performance metrics

In the PGS Catalog, performance metrics have been catalogued and have an associated identifier that starts with the prefix "PPM". To retrieve the performance metrics associated with one assessment of a polygenic score, you can use directly its identifier:

library(quincunx)

get_performance_metrics(ppm_id = 'PPM000001')

Searching by PGS identifier

Alternatively, you could also search by the associated PGS identifier, i.e. "PGS000001":

get_performance_metrics(pgs_id = 'PGS000001')

As you can see, when you search by 'PGS000001', we get multiple PPM identifiers (PPM000001 included). This is because a PGS could have been assessed multiple independent times, each assessment resulting in its own performance metrics data entry, with its own associated identifier.

Vectorised search

The function get_performance_metrics() is vectorised over ppm_id and pgs_id and you could readily retrieve performance metrics for a set of polygenic scores by providing a vector of identifiers (e.g. PGSes 42 thru 46):

ppm <- get_performance_metrics(pgs_id = sprintf("PGS%06d", 42:46))
print(ppm@performance_metrics, n = Inf)

maialab/quincunx documentation built on Aug. 18, 2022, 5:31 a.m.