Genome-wide association studies of ischemic stroke based on interpretable machine learning.

Despite the identification of several dozen genetic loci associated with ischemic stroke (IS), the genetic bases of this disease remain largely unexplored. In this research we present the results of genome-wide association studies (GWAS) based on classical statistical testing and machine learning algorithms (logistic regression, gradient boosting on decision trees, and tabular deep learning model TabNet). To build a consensus on the results obtained by different techniques, the Pareto-Optimal solution was proposed and applied.

Evaluation of Density-Based Spatial Clustering for Identifying Genomic Loci Associated with Ischemic Stroke in Genome-Wide Data.

The genetic architecture of ischemic stroke (IS), which is one of the leading causes of death worldwide, is complex and underexplored. The traditional approach for associative gene mapping is genome-wide association studies (GWASs), testing individual single-nucleotide polymorphisms (SNPs) across the genomes of case and control groups. The purpose of this research is to develop an alternative approach in which groups of SNPs are examined rather than individual ones.

The Study of the Association of Polymorphisms in , , , , , and Genes with the Risk and Outcome of Ischemic Stroke in the Russian Population.

To date, there has been great progress in understanding the genetic basis of ischemic stroke (IS); however, several aspects of the condition remain underexplored, including the influence of genetic factors on post-stroke outcomes and the identification of causative loci. We proposed that an analysis of the results obtained from animal models of brain ischemia could be helpful. To this end, we developed a bioinformatic approach for exploring single-nucleotide polymorphisms (SNPs) in human orthologs of rat genes expressed differentially after induced brain ischemia.

Analysis of Common SNPs across Continents Reveals Major Genomic Differences between Human Populations.

Common alleles tend to be more ancient than rare alleles. These common SNPs appeared thousands of years ago and reflect intricate human evolution including various adaptations, admixtures, and migration events. Eighty-four thousand abundant region-specific alleles (ARSAs) that are common in one continent but absent in the rest of the world have been characterized by processing 3100 genomes from 230 populations.

Examination of Genetic Variants Revealed from a Rat Model of Brain Ischemia in Patients with Ischemic Stroke: A Pilot Study.

Although there has been great progress in understanding the genetic bases of ischemic stroke (IS), many of its aspects remain underexplored. These include the genetics of outcomes, as well as problems with the identification of real causative loci and their functional annotations. Therefore, analysis of the results obtained from animal models of brain ischemia could be helpful.

A Workflow for Selection of Single Nucleotide Polymorphic Markers for Studying of Genetics of Ischemic Stroke Outcomes.

In this paper we propose a workflow for studying the genetic architecture of ischemic stroke outcomes. It develops further the candidate gene approach. The workflow is based on the animal model of brain ischemia, comparative genomics, human genomic variations, and algorithms of selection of tagging single nucleotide polymorphisms (tagSNPs) in genes which expression was changed after ischemic stroke.

Global Picture of Genetic Relatedness and the Evolution of Humankind.

We performed an exhaustive pairwise comparison of whole-genome sequences of 3120 individuals, representing 232 populations from all continents and seven prehistoric people including archaic and modern humans. In order to reveal an intricate picture of worldwide human genetic relatedness, 65 million very rare single nucleotide polymorphic (SNP) alleles have been bioinformatically processed. The number and size of shared identical-by-descent (IBD) genomic fragments for every pair of 3127 individuals have been revealed.

imputeqc: an R package for assessing imputation quality of genotypes and optimizing imputation parameters.

Background: The imputation of genotypes increases the power of genome-wide association studies. However, the imputation quality should be assessed in each particular case. Nevertheless, not all imputation softwares control the error of output, e.

NIPT Technique Based on the Use of Long Chimeric DNA Reads.

Non-invasive prenatal testing (NIPT) for aneuploidy on Chromosomes 21 (T21), 18 (T18) and 13 (T13) is actively used in clinical practice around the world. One of the limitations of the wider implementation of this test is the high cost of the analysis itself, as high-throughput sequencing is still relatively expensive. At the same time, there is an increasing trend in the length of reads yielded by sequencers.

Genomic landscape of the signals of positive natural selection in populations of Northern Eurasia: A view from Northern Russia.

Natural selection of beneficial genetic variants played a critical role in human adaptation to a wide range of environmental conditions. Northern Eurasia, despite its severe climate, is home to lots of ethnically diverse populations. The genetic variants associated with the survival of these populations have hardly been analyzed.