Representativeness of variation benchmark datasets.

ABSTRACT:

Background

Benchmark datasets are essential for both method development and performance assessment. These datasets have numerous requirements, representativeness being one. In the case of variant tolerance/pathogenicity prediction, representativeness means that the dataset covers the space of variations and their effects.

Results

We performed the first analysis of the representativeness of variation benchmark datasets. We used statistical approaches to investigate how proteins in the benchmark datasets were representative for the entire human protein universe. We investigated the distributions of variants in chromosomes, protein structures, CATH domains and classes, Pfam protein families, Enzyme Commission (EC) classifications and Gene Ontology annotations in 24 datasets tha

SUBMITTER: Schaafsma GCP 

PROVIDER: S-EPMC6267811 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature