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We provide a general framework for association testing with rare variants by combining mutation information across multiple variant sites within a gene and relating the enriched genetic information to disease phenotypes through appropriate regression models.
In general, considering multiple variant sites at once by comparing haplotypes increases SNV calling accuracy.
While our analysis is presented in the context of SNV calling using ShoRAH, the insights into SNV calling via probabilistic clustering should be applicable to any method that considers multiple variant sites simultaneously.
There are various versions of the collapsing method, and all combine information across multiple variant sites into a univariate test for disease association with an accumulation of rare variants.
Instead of examining the association of each rare variant in isolation, multivariate methods that combine information across multiple variant sites within a gene or other functional genomic region are a viable alternative strategy (Fig. 1).
By statistical modelling, we show that if multiple variant sites are considered at once, SNVs can be called reliably from high coverage viral deep sequencing data at frequencies lower than the error rate of the sequencing technology, and that SNV calling accuracy increases as true sequence diversity within a read length increases.
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It suggested that ERα and ERβ have opposite transcriptional effects at AP1 sites when complexed with E2. 8, 9 Multiple variant forms of ERβ were detected in 1998.
The number of variants exceeded the number of sites because multiple variants could exist at any given site.
For association testing with rare variants, it is customary to aggregate information across several variant sites within a gene to enrich association signals and to reduce the penalty of multiple testing.
For variant sites with β>0 we expect to have high nucleotide qualities, good read positions and few multiple hits also for the mismatch bases.
Multiple variant affinities were determined with the same protocol used for point-variant affinities.
Related(20)
multiple mutation sites
multiple modification sites
multiple different sites
multiple variable sites
several variant sites
multiple variant components
multiple variant genes
multiple variant opas
multiple variant transmissions
multiple variant codons
multiple variant scores
multiple variant callers
multiple variant transcripts
multiple variant strains
multiple variant forms
multiple variant loci
multiple variant affinities
multiple variant recipes
multiple variant annotations
multiple variant motifs
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