Titlebook: Epistasis; Methods and Protocol Ka-Chun Wong Book 2021 Springer Science+Business Media, LLC, part of Springer Nature 2021 Synthetic genetic

缺乏

/, Noise in CMOS Integrated Circuitstroduce a powerful and efficient statistical method, called W-test, for genetic epistasis testing. A wtest R package is developed for the implementation of the W-test method, which provides various functions to measure the main effect, pairwise interaction, higher-order interaction, and cis-regulati

公理

Analog Design for CMOS VLSI Systemsrectly is critical to understanding the genotype–phenotype map. However, inference of genetic interactions is challenging compared to inference of individual allele effects due to low statistical power. Furthermore, genetic interactions can appear inconsistent across different quantitative traits, p

palliate

Analog Device-Level Layout Automation-wide scale, screening for epistatic effects among all possible pairs of genetic markers faces two main complications. Firstly, the classical statistical methods for modeling epistasis are computationally very expensive, which makes them impractical on such large scale. Secondly, straightforward cor

pancreas

饑荒

Current Sources and Differential Pair,oping methods that enhance prediction accuracy is of major interest. Here, we provide three methods for this purpose: (1) Genomic Best Linear Unbiased Prediction (GBLUP) as a model just accounting for additive SNP effects; (2) Epistatic Random Regression BLUP (ERRBLUP) as a full epistatic model whic

Thymus

血統(tǒng)

憂傷

Psa617

https://doi.org/10.1007/978-1-4614-6163-0ed with a phenotype, the nominal statistical evidence will be inflated. Corrections are available but computationally expensive for genome-wide studies. We provide a first-order correction that can be applied in practice with essentially no additional computational cost.

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