ArticleInternational journal of molecular sciences2024
Highly Efficient Methods with a Generalized Linear Mixed Model for the Quantitative Trait Locus Mapping of Resistance to Columnaris Disease in Rainbow Trout (
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Linear mixed models (LMMs) are commonly used in genome-wide association studies (GWASs) to evaluate population structures and relatedness. However, LMMs have been shown to be ineffective in controlling false positive errors for the analysis of resistance to Columnaris disease in Rainbow Trout. To solve this problem, we conducted a series of studies using generalized linear mixed-model association software such as GMMAT (v1.4.0) (generalized linear mixed-model association tests), SAIGE (v1.4.0) (Scalable and Accurate Implementation of Generalized mixed model), and Optim-GRAMMAR for scanning a total of 25,853 SNPs. Seven different SNPs (single-nucleotide polymorphisms) associated with the trait of resistance to Columnaris were detected by Optim-GRAMMAR, four SNPs were detected by GMMAT, and three SNPs were detected by SAIGE, and all of these SNPs can explain 8.87% of the genetic variance of the trait of resistance to Columnaris disease. The heritability of the trait of resistance to Columnaris re-evaluated by GMMAT was calibrated and was found to amount to a total of 0.71 other than 0.35, which was seriously underestimated in previous research. The identification of
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.