Sentence examples for fitting markers from inspiring English sources

Linkage groups were constructed and ordered with a linkage LOD of at least 6.0, a minimum recombination fraction of 0.35, and a jump threshold of 5. SNPs exhibiting "suspect linkage" to several loci within their assigned group (as determined by JoinMap), poorly fitting markers within an ordered group, and markers that greatly inflated the linkage group size were dropped from the final mapping.

With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers.

Poorly fitting markers that greatly inflated the map length or resulted in too many double recombinations were dropped during the mapping process.

For five framework maps, we exclude obviously poorly fitting markers, which are microsatellite DNA markers in seven of 17 cases.

The cap and goggles now have fit markers, which allow the athletes to feel if they're aligned properly without using a mirror.

In each iteration of a Monte Carlo Markov Chain, every SNP was subjected to a likelihood ratio test that determined the probability that SNP would be included in the model given the fixed effects and currently fitted markers, and that SNP was then included in the model in that iteration with the calculated probability.

Saatchi et al. [ 32] in a study on Hereford beef cattle showed that, with BayesC, accuracies of genomic predictions increased as π increased from 0 to 0.95 and 0.99 (fewer fitted markers in the model) for almost all studied traits.

In this case, the marker effects were derived using RR since this method allows fitting all markers simultaneously in the model (i.e. taking LD into account), with the same penalization across the genome (i.e. no marker-specific shrinkage).

Briefly shrinkage methods work by forcing some of the marker effects with trivial effects to 0. Different approaches for shrinking are available allowing fitting all markers simultaneously.

The other two methods involved fitting all markers simultaneously as random effects, modeled in a Bayesian framework [ 21].

Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously.