PreFer Genes (Prediction of Fertility Genes) aims at providing a basis for filtering out the most prospective candidates for diagnosis and - in the long term - treatment of male fertility impairment from the large number of possible genes/proteins. Some of the top-ranked candidates may also be worthwhile targets for the development of novel contraceptives.
For this purpose, PreFer Genes assigns a probability score to genes, which is based on binary logistic regression analyses. This value indicates the predicted Fertility Relevance Probability (FRP), i.e., the probability that a gene is associated with male sub- or infertility when mutated, deleted, or dysregulated.
Logistic regressions were carried out on two datasets, which were categorized based on different sources:
In the dataset named Murine Phenotypes, the initial categorization of genes is based on phenotypes of male knockout mice homozygous or hemizygous for targeted mutations as reported by MGI (Mouse Genome Informatics).
Genes contained in dataset Human Phenotypes were classified as either associated or not associated with male fertility based on literature concerning humans.
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