Sentence examples for marker data with from inspiring English sources

The phylogeny analysis was complemented with 10,000 bootstrapping replicas on the entire marker data with random replacements.

The potential genotyping errors and missing genotypes were inferred by using information from flanking marker data with the initial marker order.

The total number of haploblocks and the related variables for each D′ threshold, obtained from the HD marker data with 492,057 SNPs are presented in Table 2.

It is further necessary to understand the distribution of neutral allele frequencies under the specified model, in order to compare observed marker data with the distribution expected under the null hypothesis.

LOD thresholds corresponding to a genome-wide type I error rate of α = 5% were determined using 1,000 permutations of traits over marker data, with cofactors reselected for each permuted data set, using QTLCartographer 1.17 [ 53, 54].

Conventional selection methods exploit phenotypes of the individual and/or of its relatives', e.g. using best linear unbiased prediction (BLUP) [ 3, 4], whereas GS combines marker data with phenotypic and pedigree data (when available), which increases the accuracy of prediction.

An earlier study by Ødegård and Meuwissen [ 1] described how identity-by-descent (IBD) genomic selection (IBD-GS) for a Gaussian trait can use sparse marker data combined with selective genotyping of the phenotypically best families and the sibs with the most extreme (high/low) phenotypes within these families.

Thus, integration of surrogate marker data along with imaging studies was crucial for assessing the OBD of recombinant human endostatin.

We addressed some of these questions by analysing molecular marker data along with niche modelling tools, and investigated the contribution of environmental selection and genetic drift to L. camara invasion in India.

In contrast, the accuracy of prediction of genomic selection based on the data sets imputed with the map-dependent algorithm IMPUTE2 outperformed the accuracy of prediction of genomic selection based on the original 9 k SNP marker data even with a small reference population size of 50 out of 371 individual lines.

RILs with SNP marker data in agreement with RFLP/SSR data were kept for the subsequent analyses.