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In their review of the first five years of genome-wide association studies (GWAS), Visscher et al. [ 5] countered the perception in some circles that common variant analysis has had little utility because it is rarely clinically actionable, by observing the gains in knowledge of new biology have been unprecedented.
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Many recent methods developed for rare and common variant analysis have been geared toward determining the optimal weights for the different variants.
Genotype cluster plot inspection was not possible at the genome-wide scale, so we inspected the clustering properties of SNPs within signals of interest after the rare variant analysis had been carried out.
As several rare genomic variants have been shown to affect common phenotypes, rare variants association analysis has received considerable attention.
Statistical genetics considerations of rare variant association analysis have been the focus of intensive method development over the last few years.
Considering the limited number of available cases and controls in this study, it is obvious that our statistical evaluation had to be limited to common variants while rare variant analysis would have lacked sufficient statistical power.
However, no systematic analysis has examined germline variants affecting cancer risk to identify, which may affect alternative splicing.
RUbioSeq's variant analysis results have been already validated and published.
Further, analysis has shown that both the variants have polyadenylation signals followed by poly(A) tail upstream 30 and 16 nucleotides for variants -01 & -02, respectively.
This analysis has identified novel possible BP susceptibility variants in both of these genes.
This analysis has looked at the performance of new variants of predictive models for case finding.
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