Sentence examples for more flexible analyses from inspiring English sources

However, to implement more flexible analyses, such as parent-of-origin analyses, we also used an in-house program written for family-based association (49) that implements methods described by Cordell et al. (50).

The design of NetWalker and of the NetWalker Interactome Knowledgebase to emphasize whole-distribution based analysis methods (see Manual for more details) for more flexible data analyses and model building is its most distinguishing feature from other software.

The use of IPD will allow for more appropriate and flexible analyses of both subgroups and outcomes.

In particular, a meta-analysis using IPD can enable more flexible and detailed subgroup analyses [ 44, 45].

Because the a b model assumes constant rates of infection on each side of the threshold, which may be a strong assumption, we considered in supplementary analyses more flexible models which allowed linear, quadratic or logistic relationships on either side of the threshold.

MapNext provides four main analyses: (i) unspliced alignment and clustering of reads, (ii) spliced alignment of transcript reads over intron boundaries, (iii) SNP detection and estimation of minor allele frequency from population sequences, and (iv) storage of result data in a database to make it available for more flexible queries and for further analyses.

More flexible methods tested in sensitivity analyses confirmed similar accuracy: logistic penalised models with multiple interaction terms showed a sensitivity of 94.35 955% CI 91.36 to 96.68) and a specificity of 92.59 955% CI 90.11 to 94.68); classification trees did not identify alternative pathways capable of significantly improving accuracy for the classification of cases.

We realize that using a ridge penalty with a group penalty may be slightly redundant as the sparse group lasso gives an elastic net fit within each nonzero group, but this addition makes PeRC more flexible in terms of the analyses one can perform.

This programming paradigm was fine for the initial project but a more flexible solution was required for the analyses of the wider range of biomedical scenarios sought under the new version of the tool.

Compared with the other multivariate Copula extension methods, Pair-Copula imposes no restrictions on the selected types or parameters and is thus more flexible and practical for modelling and analysing complex dependences.

With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing.