Regarding the rights and duties of Clinical Laboratory Geneticists in genetic healthcare systems; results of a survey in over 50 countries.

Specialists of human genetic diagnostics can be divided into four groups: Medical Geneticists (MDG), Genetic Nurses and/or Counsellors (GN/GC), Clinical Laboratory Geneticists (CLG) and Laboratory Genetics Technicians (LGT). While the first two groups are in direct patient contact, the work of the latter two, of equal importance for patient care, are often hidden as they work behind the scenes. Herein the first study on the rights and duties of CLGs is presented. We present the results of a survey performed in 35 European and 18 non-European countries with 100 participating specialists. A national CLG title is available in 60% of European countries, and in 77% of the surveyed European countries a CLG can be the main responsible head of the laboratory performing human genetic tests. However, in only 20% of European countries is a lab-report valid with only a CLGs' signature - even though the report is almost always formulated by the CLG, and an interpretation of the obtained results in a clinical context by the CLG is expected in nearly 90% of European countries. Interestingly, CLGs see patients in 30% of European countries, and are also regularly involved in student education. Overall, the CLG profession includes numerous duties, which are quite similar in all regions of the world. Strikingly, the CLG's rights and responsibilities of leading a lab, or signing a report are regulated differently according to country specific regulations. Overall, the CLG is a well-recognized profession worldwide and often working within a multidisciplinary team of human genetic diagnostics professionals.

Non-parametric estimation of population size changes from the site frequency spectrum.

Changes in population size is a useful quantity for understanding the evolutionary history of a species. Genetic variation within a species can be summarized by the site frequency spectrum (SFS). For a sample of size n, the SFS is a vector of length n - 1 where entry i is the number of sites where the mutant base appears i times and the ancestral base appears n - i times. We present a new method, CubSFS, for estimating the changes in population size of a panmictic population from an observed SFS. First, we provide a straightforward proof for the expression of the expected site frequency spectrum depending only on the population size. Our derivation is based on an eigenvalue decomposition of the instantaneous coalescent rate matrix. Second, we solve the inverse problem of determining the changes in population size from an observed SFS. Our solution is based on a cubic spline for the population size. The cubic spline is determined by minimizing the weighted average of two terms, namely (i) the goodness of fit to the observed SFS, and (ii) a penalty term based on the smoothness of the changes. The weight is determined by cross-validation. The new method is validated on simulated demographic histories and applied on unfolded and folded SFS from 26 different human populations from the 1000 Genomes Project.

Two-stage test of means of unordered pairs.

The problem of testing equality of means of a bivariate normal distribution on the basis of a sample of size n has been considered when the labels of the observations are either missing or not known. The problem may arise in many applied settings, especially in genetics. Classical likelihood ratio test fails here because of identifiability problems. We propose a two-stage testing procedure using a recently developed test in the context of penalized splines. The proposed testing procedure is found to outperform the tests proposed in the literature. Copyright © 2017 John Wiley & Sons, Ltd.