Statistics – Applications
Scientific paper
2008-12-07
Statistics
Applications
Scientific paper
We propose a Model-Based Clustering (MBC) method combined with loci selection using multi-allelic loci genetic data. The loci selection problem is regarded as a model selection problem and models in competition are compared with the Bayesian Information Criterion (BIC). The resulting procedure selects the subset of clustering loci, the number of clusters, estimates the proportion of each cluster and the allelic frequencies within each cluster. We prove that the selected model converges in probability to the true model under a single realistic assumption as the size of the sample tends to infinity. The proposed method named MixMoGenD (Mixture Model using Genetic Data) was implemented using c++ programming language. Numerical experiments on simulated data sets was conducted to highlight the interest of the proposed loci selection procedure.
Gassiat Elisabeth
Toussile Wilson
No associations
LandOfFree
Model-Based Clustering using multi-allelic loci data with loci selection does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Model-Based Clustering using multi-allelic loci data with loci selection, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Model-Based Clustering using multi-allelic loci data with loci selection will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-450294