Heteroscedastic ridge regression approaches for genome-wide prediction with a focus on computational efficiency and accurate effect estimation.

Ridge regression with heteroscedastic marker variances provides an alternative to Bayesian genome-wide prediction methods. Our objectives were to suggest new methods to determine marker-specific shrinkage factors for heteroscedastic ridge regression and to investigate their properties with respect to computational efficiency and accuracy of estimated effects. We analyzed published data sets of maize, wheat, and sugar beet as well as simulated data with the new methods.

Genome-based prediction of test cross performance in two subsequent breeding cycles.

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding.

Breast ultrasound elastography--results of 193 breast lesions in a prospective study with histopathologic correlation.

Purpose: To evaluate the diagnostic performance of ultrasound elastography in breast masses.

Material And Methods: 193 lesions (129 benign, 64 malignant) were analyzed with the EUB 8500 Logos-ultrasonic-unit (Hitachi Medical, Japan) and a linear-array-transducer of 7.5-13-MHz.