Characterizing substructure via mixture modeling in large-scale genetic summary statistics.

Genetic summary data are broadly accessible and highly useful, including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into summary data, such as allele frequencies, masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted-for substructure limits summary data usability, especially for understudied or admixed populations.

The sarcoma ring trial: a case-based analysis of inter-center agreement across 21 German-speaking sarcoma centers.

Purpose: The management of soft tissue sarcoma (STS) at reference centers with specialized multidisciplinary tumor boards (MTB) improves patient survival. The German Cancer Society (DKG) certifies sarcoma centers in German-speaking countries, promoting high standards of care. This study investigated the variability in treatment recommendations for localized STS across different German-speaking tertiary sarcoma centers.

Measurements of neurite extension and nucleokinesis in an iPSC-derived model system following microtubule perturbation.

In neurons, patterns of different microtubule types are essential for neurite extension and nucleokinesis. Cellular model systems such as rodent primary cultures and induced pluripotent stem cells (iPSC)-derived neurons have provided key insights into how these patterns are created and maintained through the action of microtubule-associated proteins, motor proteins, and regulatory enzymes. iPSC-derived models show tremendous promise but lack benchmarking and validation relative to rodent primary cultures.

CCAFE: Estimating Case and Control Allele Frequencies from GWAS Summary Statistics.

Methods involving summary statistics in genetics can be quite powerful but can be limited in utility. For instance, many post-hoc analyses of disease studies require case and control allele frequencies (AFs), which are not always published. We present two frameworks to derive case and control AFs from GWAS summary statistics using the odds ratio, case and control sample sizes, and either the total (case and control aggregated) AF or standard error (SE).