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Multiple causal genes have been identified that influence the development of autoimmune disorders by genome-wide association studies (GWAS) [5].
Each includes Gene Atlas and GO enrichments, r comparisons and comparisons of results assuming a single or multiple causal genes (Supplementary Figs S7 9).
Moreover, the complex phenotype is often associated with interactions among multiple causal genes (epistasis), any of which alone is not sufficient to drive phenotypic change.
Although the difference between the TopK-Gene and CAVIAR-Gene in the case of one causal gene is negligible, we observe a 10% higher recall rate when there are multiple causal genes in a region (Fig. 2b, d, and f).
The goal of the present study was to use expression analysis and next-generation sequencing to evaluate positional candidate genes within this 3.1-Mb glucose locus, located on rat chromosome 1: 204.38–207.48 Mb, a complex region that may harbor multiple causal genes (Granhall et al. 2006; Solberg Woods et al. 2010, 2012).
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Distributional limits are complex results of multiple causal agents.
The power of these tests is reduced if there is allelic heterogeneity (multiple causal mutations in a gene), because each single-marker test is likely to tag at most one of the causal variants.
In response, a variety of methods have been developed that attempt to cluster rare variants so that they may gather strength from one another under the premise that there may be multiple causal variants within a gene.
All of these genes contained multiple causal rare variants with a moderate or high effect size.
In addition, although there may be only one disease gene in the QTL, the linkage signal may be elicited by multiple causal variants in the disease gene and in different families.
Because such variants are rare, either they must have strong effect sizes or there must be multiple causal variants clustered within a gene to have power to detect the association with a reasonably sized sample.
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