OUTRIDER: A Statistical Method for Detecting Aberrantly Expressed Genes in RNA Sequencing Data.

RNA sequencing (RNA-seq) is gaining popularity as a complementary assay to genome sequencing for precisely identifying the molecular causes of rare disorders. A powerful approach is to identify aberrant gene expression levels as potential pathogenic events. However, existing methods for detecting aberrant read counts in RNA-seq data either lack assessments of statistical significance, so that establishing cutoffs is arbitrary, or rely on subjective manual corrections for confounders. Here, we describe OUTRIDER (Outlier in RNA-Seq Finder), an algorithm developed to address these issues. The algorithm uses an autoencoder to model read-count expectations according to the gene covariation resulting from technical, environmental, or common genetic variations. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. The model is automatically fitted to achieve the best recall of artificially corrupted data. Precision-recall analyses using simulated outlier read counts demonstrated the importance of controlling for covariation and significance-based thresholds. OUTRIDER is open source and includes functions for filtering out genes not expressed in a dataset, for identifying outlier samples with too many aberrantly expressed genes, and for detecting aberrant gene expression on the basis of false-discovery-rate-adjusted p values. Overall, OUTRIDER provides an end-to-end solution for identifying aberrantly expressed genes and is suitable for use by rare-disease diagnostic platforms.

[Cardiovascular prevention in Saxony-Anhalt : Necessity and new perspectives]. / Kardiovaskuläre Prävention in Sachsen-Anhalt : Notwendigkeit und neue Perspektiven.

Cardiovascular risk factors (high blood pressure, smoking, overweight, type 2 diabetes, dyslipidemia, physical inactivity) substantially rise with increasing age, particularly after middle age, whereby women are affected to a much greater extent. In the population of Saxony-Anhalt the prevalence of cardiovascular risk factors is clearly increased and the population structure in Saxony-Anhalt is particularly characterized by a high average age as well as high morbidity and mortality rates due to cardiovascular diseases. Saxony-Anhalt therefore provides a model character for the demographic development in Europe. This review article discusses strategies for the implementation of target group-specific cardiovascular preventive strategies in the Federal State of Saxony-Anhalt with special consideration of age and sex. When preventive medicine facilities are established and innovative treatment possibilities for patients with cardiovascular risks are created, prevention should also become available in rural areas.