The Survival Kit
The Survival Kit is primarily intended to fill a gap in the software available to animal breeders who generally tend to use extremely large data sets and want to estimate random effects. Methods of survival analysis have primarily been developed in the area of clinical biometrics where data sets and number of levels of effects are usually smaller.
Although developed by animal breeders for animal breeders, the programs of the Survival Kit could be interesting for people from other areas encountering similar problems of large models and random effects. To make the Survival Kit user-friendly, commands used in the parameter files mimic the SAS command language. more
GRain (version 2.1) is software intended to enable and promote testing of various hypotheses with respect to purging and heterogeneity of inbreeding depression.
The program is based on a stochastic approach, the gene dropping method, and calculates various individual coefficients from large and complex pedigrees. To test the purging of inbreeding depression, GRain calculates, together with the “classical” inbreeding coefficient, ancestral inbreeding coefficients proposed by Ballou (1997) and Kalinowski et al. (2000) as well as an ancestral history coefficient, defined here for the first time.
Ancestral history coefficient quantifies the frequency that an allele has undergone Identical by Descent (IBD) status in the past. Furthermore, GRain enables testing of heterogeneity and/or purging of inbreeding depression with respect to different founders/ancestors as it calculates partial coefficients for all previously obtained coefficients.
Detailed description of the program methods, input and output files is provided in the paper:
Roswitha Baumung, János Farkas, Didier Boichard, Gábor Mészáros, Johann Sölkner, Ino Curik (2015): GRAIN: A computer program to calculate ancestral and partial inbreeding coefficients using a gene dropping approach. Journal of Animal Breeding and Genetics, 132, 100–108. doi:10.1111/jbg.12145
BENDOPT and BENDPDF are two computer programs implementing different approaches of the so-called "BENDING" procedure (Hayes and Hill, 1981).
In BENDOPT, the appropriate bending factor is either chosen by an optimized procedure (Essl, 1991), which requires some prior knowledge, or may be preselected by the user in dependence of some sample properties. This approach was primarily intended to improve poorly estimated variance-covariance matrices for index selection purposes. However, this procedure can also be applied quite generally to any genetic variance-covariance matrix obtained from a small or poorly structured sample to get more reliable parameter-estimates (e.g. heritabilites and genetic correlations between traits). more