EigenGWAS: An online visualizing and interactive application for detecting genomic signatures of natural selection

Abstract

Detecting genetic regions under selection in structured populations is of great importance in ecology, evolutionary biology and breeding programmes. We recently proposed EigenGWAS, an unsupervised genomic scanning approach that is similar to F ST but does not require grouping information of the population, for detection of genomic regions under selection. The original EigenGWAS is designed for the random mating population, and here we extend its use to inbred populations. We also show in theory and simulation that eigenvalues, the previous corrector for genetic drift in EigenGWAS, are overcorrected for genetic drift, and the genomic inflation factor is a better option for this adjustment. Applying the updated algorithm, we introduce the new EigenGWAS online platform with highly efficient core implementation. Our online computational tool accepts plink data in a standard binary format that can be easily converted from the original sequencing data, provides the users with graphical results via the R-Shiny user-friendly interface. We applied the proposed method and tool to various data sets, and biologically interpretable results as well as caveats that may lead to an unsatisfactory outcome are given. The EigenGWAS online platform is available at www.eigen gwas.com, and can be localized and scaled up via R (recommended) or docker.

Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm

“…Interactive genetic algorithm has a wide application prospect in different fields, including portfolio optimization [ 1 ], clothing customization [ 2 ], communication system combination [ 3 ], gene selection [ 4 ], and information storage [ 5 ]. In view of the existing problems in genetic target combination optimization, fuzzy neural network and intelligent recognition model were used to extract the original data based on the relevant theories of interactive genetic algorithm [ 6 ].…”

The STROMICS genome study: deep whole-genome sequencing and analysis of 10K Chinese patients with ischemic stroke reveal complex genetic and phenotypic interplay

“…Knowledge of the genetic structure and history provides essential information for disease study using association tests 31 and has not yet been assessed among the STROMICS patients. We applied genetic methods including principal component analysis (PCA) 32 , ADMIXTURE 33 , and PC-based selection 34 to quantify the population structure and identify recent positive selection using the WGS data from STROMICS.…”

“…Genetic variants in the PC-based selection analysis were SNVs with MAF > 1% and R 2 < 0.9 in a sliding window of 50 SNVs with 5 SNVs as a step among the population of 9947 Han individuals. First, the top 10 eigenvalues and their corresponding eigenvectors were calculated by ProPCA 80 , a component of EigenGWAS 34 . Second, the SNV effects, which were nearly equivalent to F ST , were estimated by regressing the genotypes of each SNV with a selected eigenvector.…”

Sequencing an F1 hybrid of Silurus asotus and S. meridionalis enabled the assembly of high-quality parental genomes

“…The contig N50 length of the two parental genome reached 6.75 Mb and 9.78 Mb, and this was much longer than that of P. fulvidraco and G. maculatum , which were 1.1 Mb and 993.67 kb, respectively 25 , 42 . However, the contig N50 length of a recently reported S. meridionalis genome reached 13.19 Mb may suggest the superiority of the Nanopore sequencing technology 43 . We suppose that the contig N50 length is one thing, and the correctness of assembly should be more important.…”