Seminar 26 Sept: Modelling rate of decline (slope) of a biomarker as a quantitative genetic trait using mixed effects models: application to loss of renal function (GFR) in type 1 diabetes
Members of the UGI have contributed towards the following software packages:
- LDAK – improved SNP-based heritability analysis
Software for investigating the genetic architecture of complex traits and diseases.
- Colocalisation of GWAS/eQTL signals to identify shared biological mechanisms
Compares association study p-values (e.g. from testing a biomarker), with liver or brain expression data outputting a posterior probability for a common signal within a region defined by the expression probe (200Kb upstream and downstream from the probe).
- bnlearn - Bayesian network learning
An R package for learning the graphical structure of Bayesian networks, estimating their parameters and performing some useful inference
- LikeLTD - Evaluation of mixed-source, low-template DNA profiels in forensic science
An R package for computing likelihoods for DNA profile evidence, including complex mixtures and when profiles are subject to dropout.
- FastMixedModel - fast inference in linear mixed effects models
Incorporated within the MixABEL R package, within the GenABEL suite of software.
- HyperLASSO - Simultaneious analysis of genome-wide SNP data
FREGENE - simulate sequence-like data in large genomic regions and large populations. Released as part of BARGEN (Bioinformatics for the Analysis and Exploitation of Resequenced Genomes).
- David Balding has also been involved in the population genetics softwares HapCluster, BayesFST, Mac5 and BATWING
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