In Section "Results and Discussion", we detail the experimental results obtained on biological DNA sequences, comparing different algorithmic strategies for filtering, including strategies used in other tools like SWIFT[ 6].
Two main strategies for filtering include: (1) limiting the interaction analyses to only include one or more variants that have demonstrated an association with the trait through GWAS or candidate gene studies; and (2) filtering SNPs based on biologically established gene-gene interactions [Sun et al., 2014].
We examined the benefit of a commonly used strategy that has already been applied for filtering environmental contamination from Neandertal NGS reads [ 29] but also in many other contexts (e.g. expression profiling) [ 30].
We elaborate on results about the approximation of nonlinear systems and their optimal control, and then combine the theoretical conclusions together with numerical strategies for identification, filtering, and updating, which take into account possible changes in the structure or the values of the coefficients of the original system.
Beginning with 76,712 variants with a reliable coverage identified in the exome of the patient, it is essential to carefully consider strategies for successfully filtering pathogenic variants.
Basking sharks, whale sharks, and megamouth sharks have independently evolved different strategies for filter feeding plankton: basking sharks practice ram feeding, whale sharks use suction to take in plankton and small fishes, and megamouth sharks make suction feeding more efficient by using the luminescent tissue inside of their mouths to attract prey in the deep ocean.
To deal with these problems caused by non-contiguous and dynamically changing spectrum, a resource block (RB) strategy for the filtering approach is proposed in [14].
Here we present a strategy to filter for SNPs representing orthologous loci.
We present a conservative strategy to filter for unique loci by using the putative allelic variation across all individuals under study to identify the minimum number of haplotypes within individuals.
This paper proposes a simplified tuning strategy for the multivariable filtered Smith predictor.
