Packages

GenABEL, or *ABEL, is an umbrella name for a number of software packages aiming to facilitate statistical analyses of polymorphic genomes data. This is reach program set which now allows very flexible genome-wide association (GWA) analysis (GenABEL, ProbABEL, MixABEL, OmicABEL), meta-analysis (MetABEL), parallelization of GWA analyses (ParallABEL), management of very large files (DatABEL), and facilitates evaluation of prediction (PredictABEL).

Most likely, you only need one of the packages for your specific task. Figure out which one you need, install, and use! If you have questions, please refer to the "Support" section of this web-site.

The code for latest development versions of all packages are available from GenABEL on R-forge

For stable releases, use CRAN version for R packages or links provided at this web-site

GenABEL

Genome-wide association analysis for quantitative, binary and time-till-event traits

MetABEL

Meta-analysis of genome-wide SNP association results Genome-wide association analysis for quantitative, binary and time-till-event traits

ProbABEL

Genome-wide association analysis of imputed data

PredictABEL

Assess the performance of risk models for binary outcomes

DatABEL

File-based access to large matrices stored on HDD in binary format

ParallABEL

Generalized parallelization of Genome-Wide Association Studies

MixABEL

More mixed models for genome-wide association analysis; experimenting with GSL, multiple input formats, iterator, parallelization through threads.

VariABEL

Genome-wide variance heterogeneity analysis as a tool for identification of potentially interacting SNPs.

OmicABEL

Rapid mixed-model based GWAS efficiently handling large datasets, and both single trait and multiple trait ("omics") analyses