ReviewJournal of biomedical research2015
Statistical analysis for genome-wide association study.
Review in Journal of biomedical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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
53 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes.International journal of molecular sciences · 2020Pooled it
- Trial
- Identification of Genomic Regions for Partial Resistance to Soybean Rust Under Field Conditions Using FarmCPU and Machine Learning Approaches.Plants (Basel, Switzerland) · 2026Article
- A rapid review of genetic association studies of parent-of-origin effects and fetal growth.Molecular and cellular pediatrics · 2026Review
- An integrative association analysis for complex diseases in underrepresented groups by leveraging the trans-ethnic genetic similarity.Briefings in bioinformatics · 2026Article
- Method for the Dissection of Genomic Loci Associated with Chickpea Root Penetration Traits in Compact Soil.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Unraveling the impact of neonatal jaundice on allergic diseases: a Mendelian randomization study.Archives of medical science : AMS · 2026Article
- Generative prediction of causal gene sets responsible for complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Integrative transcriptogenomic analyses reveal the regulatory network underlying rice eating and cooking quality and identify a role for alpha-globulin in modulating starch and sucrose metabolism.Plant communications · 2025Article
- Influence and role of polygenic risk score in the development of 32 complex diseases.Journal of global health · 2025Article
- Breastfeeding, genetic susceptibility, and the risk of asthma and allergic diseases in children and adolescents: a retrospective national population-based cohort study.BMC public health · 2024Article
- GWAS for identification of genomic regions and candidate genes in vegetable crops.Functional & integrative genomics · 2024Review
- Causal effects of cardiovascular health on five epigenetic clocks.Clinical epigenetics · 2024Article
- Incorporating genetic similarity of auxiliary samples into eGene identification under the transfer learning framework.Journal of translational medicine · 2024Article
- Clinical Strategies in Gene Screening Counseling for the Healthy General Population.Korean journal of family medicine · 2024Article
- Article
- Article
- Article
- Testing the Utility of Polygenic Risk Scores for Type 2 Diabetes and Obesity in Predicting Metabolic Changes in a Prediabetic Population: An Observational Study.International journal of molecular sciences · 2022Observational
- Transfer learning for genotype-phenotype prediction using deep learning models.BMC bioinformatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the past few years, genome-wide association study (GWAS) has made great successes in identifying genetic susceptibility loci underlying many complex diseases and traits. The findings provide important genetic insights into understanding pathogenesis of diseases. In this paper, we present an overview of widely used approaches and strategies for analysis of GWAS, offered a general consideration to deal with GWAS data. The issues regarding data quality control, population structure, association analysis, multiple comparison and visual presentation of GWAS results are discussed; other advanced topics including the issue of missing heritability, meta-analysis, set-based association analysis, copy number variation analysis and GWAS cohort analysis are also briefly introduced.
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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 OpenQuestion graph.