Sentence examples for dataset likelihood from inspiring English sources

For each dataset, likelihood ratio tests (LRT) for detection of positive selection were examined using M7-M8 and M8a-M8 comparisons.

In order to visualize conflicting phylogenetic signal in our dataset, likelihood mapping and four-cluster likelihood mapping analyses were completed using the program Tree Puzzle [ 64].

We identified a significant excess of approximate and exact indels at the expense of unique indels in the observed dataset (Likelihood Ratio (LR) χ2 = 916, 2 d.f., P < 0.0001; Table S1(see Additional file 1) and Fig. 2).

For each dataset, Maximum Likelihood (ML) phylogenetic trees were computed with PHYML using the JTT model and a gamma correction to take into account the heterogeneity of evolutionary rates across sites (4 discrete classes of sites, an estimated alpha parameter and an estimated proportion of invariable sites) [48].

Eighty-three SNP-SNP models replicated in the independent dataset at likelihood ratio test P < 0.05.

For each dataset, one Likelihood Ratio Test (LRT) was performed for dN/ dS heterogeneity across codons (M0/M3 test).

In 76 of the 100 simulated datasets, raw likelihood values were greater for the IM model, by an average of just over one log-likelihood unit.

We analyzed the site models and branch-site models on the large and small datasets with likelihood ratio tests (LRT), respectively.

Two graphical approaches were employed to explore the phylogenetic signal in each data partition and combined datasets, the Likelihood Mapping (LM) [ 116] as implemented in TREE- PUZZLE, and the consensus networks [ 117] using trees generated by bootstrap re-sampling in SplitsTree4 V4.13.1 [ 118].

For three datasets, −2×log-likelihood and goodness-of-fit for the non-symmetrical models were almost identical to the symmetrical models.

The program SEQBOOT from the PHYLIP [ 95] package was used to generate 100 pseudoreplicate datasets, maximum-likelihood trees were estimated for each replicate using the program PHYML [ 96] and consensus trees were inferred using the program CONSENSE.