ABEILLE: a novel method for ABerrant Expression Identification empLoying machine LEarning from RNA-sequencing data.
Journal:
Bioinformatics (Oxford, England)
PMID:
36063052
Abstract
MOTIVATION: Current advances in omics technologies are paving the diagnosis of rare diseases proposing a complementary assay to identify the responsible gene. The use of transcriptomic data to identify aberrant gene expression (AGE) has demonstrated to yield potential pathogenic events. However, popular approaches for AGE identification are limited by the use of statistical tests that imply the choice of arbitrary cut-off for significance assessment and the availability of several replicates not always possible in clinical contexts.