RAREMETAL: fast and powerful meta-analysis for rare variants.
paper
Cited
Public
- Authors
- Feng, Shuang; Liu, Dajiang; Zhan, Xiaowei; Wing, Mary Kate; Abecasis, Gonçalo R
- Year
- 2014
- Journal
- Bioinformatics (Oxford, England)
- PMID
- 24894501
- DOI
- 10.1093/bioinformatics/btu367
- PMCID
- PMC4173011
SUMMARY: RAREMETAL is a computationally efficient tool for meta-analysis of rare variants genotyped using sequencing or arrays. RAREMETAL facilitates analyses of individual studies, accommodates a variety of input file formats, handles related and unrelated individuals, executes both single variant and burden tests and performs conditional association analyses. AVAILABILITY AND IMPLEMENTATION: http://genome.sph.umich.edu/wiki/RAREMETAL for executables, source code, documentation and tutorial.
Automatically generated QQ and Manhattan plots by RAREMETAL and RMW. (a) Manhattan plot from single variant analysis. (b) Manhattan plot from gene-level burden tests
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| Scalable and accurate rare variant meta-analysis with Meta-SAIGE. | Park E et al. | — | 2025 | → |
| RAVAR: a curated repository for rare variant-trait associations. | Cao C et al. | — | 2024 | → |
| From SNP to pathway-based GWAS meta-analysis: do current meta-analysis approaches resolve power and replication in genetic association studies? | Defo J et al. | — | 2023 | → |
| Identifying high-impact variants and genes in exomes of Ashkenazi Jewish inflammatory bowel disease patients. | Wu Y et al. | — | 2023 | → |
| Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. | Li X et al. | — | 2023 | → |
| Strategies in Aggregation Tests for Rare Variants. | Rajabli F et al. | — | 2023 | → |
| The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits. | Costanzo MC et al. | — | 2023 | → |
| Trumpet plots: visualizing the relationship between allele frequency and effect size in genetic association studies. | Corte L et al. | — | 2023 | → |
| Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants. | Young KL et al. | — | 2023 | → |
| A multiethnic whole genome sequencing study to identify novel loci for bone mineral density. | Greenbaum J et al. | — | 2022 | → |
| A saturated map of common genetic variants associated with human height. | Yengo L et al. | — | 2022 | → |
| Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways. | Young WJ et al. | — | 2022 | → |
| Genetic variants associated with longitudinal changes in brain structure across the lifespan. | Brouwer RM et al. | — | 2022 | → |
| Strong and weak cross-inheritance of substance use disorders in a nationally representative sample. | Zhang H et al. | — | 2022 | → |
| Whole-exome sequencing identifies novel protein-altering variants associated with serum apolipoprotein and lipid concentrations. | Sandholm N et al. | — | 2022 | → |
| An atlas of mitochondrial DNA genotype-phenotype associations in the UK Biobank. | Yonova-Doing E et al. | — | 2021 | → |
| An evaluation of approaches for rare variant association analyses of binary traits in related samples. | Chen MH et al. | — | 2021 | → |
| Bayesian model comparison for rare-variant association studies. | Venkataraman GR et al. | — | 2021 | → |
| Genetic analyses of the QT interval and its components in over 250K individuals identifies new loci and pathways affecting ventricular depolarization and repolarization | Young WJ et al. | — | 2021 | — |
| Identification of putative causal loci in whole-genome sequencing data via knockoff statistics. | He Z et al. | — | 2021 | → |
| Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer's dementia. | Tang S et al. | — | 2021 | → |
| Rare variant analysis in eczema identifies exonic variants in DUSP1, NOTCH4 and SLC9A4. | Grosche S et al. | — | 2021 | → |
| The Contribution of Known Familial Cardiovascular Disease Genes to Sudden Cardiac Death in Patients Undergoing Hemodialysis. | Schwantes-An TH et al. | — | 2021 | → |
| The power of genetic diversity in genome-wide association studies of lipids. | Graham SE et al. | — | 2021 | → |
| A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness. | Dauber A et al. | — | 2020 | → |
| Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data. | Jiang Y et al. | — | 2020 | → |
| Family-based exome sequencing identifies rare coding variants in age-related macular degeneration. | Ratnapriya R et al. | — | 2020 | → |
| GEN2VCF: a converter for human genome imputation output format to VCF format. | Shin DM et al. | — | 2020 | → |
| Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity. | Yaghootkar H et al. | — | 2020 | → |
| Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. | Erzurumluoglu AM et al. | — | 2020 | → |
| Association of Early-Onset Alzheimer Disease With Elevated Low-Density Lipoprotein Cholesterol Levels and Rare Genetic Coding Variants of APOB. | Wingo TS et al. | — | 2019 | → |
| Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology. | Spracklen CN et al. | — | 2019 | → |
| metaFARVAT: An Efficient Tool for Meta-Analysis of Family-Based, Case-Control, and Population-Based Rare Variant Association Studies. | Wang L et al. | — | 2019 | → |
| Novel genetic loci affecting facial shape variation in humans. | Xiong Z et al. | — | 2019 | → |
| Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution. | Justice AE et al. | — | 2019 | → |
| Rare-variant collapsing analyses for complex traits: guidelines and applications. | Povysil G et al. | — | 2019 | → |
| Regional fat depot masses are influenced by protein-coding gene variants. | Neville MJ et al. | — | 2019 | → |
| Targeted deep sequencing of the PEAR1 locus for platelet aggregation in European and African American families. | Keramati AR et al. | — | 2019 | → |
| An exome-wide sequencing study of lipid response to high-fat meal and fenofibrate in Caucasians from the GOLDN cohort. | Geng X et al. | — | 2018 | → |
| Association Between Population Density and Genetic Risk for Schizophrenia. | Colodro-Conde L et al. | — | 2018 | → |
| Copy Number Variation. | Macé A et al. | — | 2018 | → |
| Deep-coverage whole genome sequences and blood lipids among 16,324 individuals. | Natarajan P et al. | — | 2018 | → |
| General retrospective mega-analysis framework for rare variant association tests. | Chien LC et al. | — | 2018 | → |
| Improved score statistics for meta-analysis in single-variant and gene-level association studies. | Yang J et al. | — | 2018 | → |
| Meta-Analysis of Common and Rare Variants. | Michailidou K | — | 2018 | → |
| No evidence of association of oxytocin polymorphisms with breastfeeding in 2 independent samples. | Colodro-Conde L et al. | — | 2018 | → |
| Nonsynonymous Variants in <i>PAX4</i> and <i>GLP1R</i> Are Associated With Type 2 Diabetes in an East Asian Population. | Kwak SH et al. | — | 2018 | → |
| Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes. | Jiang Y et al. | — | 2018 | → |
| Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. | Turcot V et al. | — | 2018 | → |
| Analysis of potential protein-modifying variants in 9000 endometriosis patients and 150000 controls of European ancestry. | Sapkota Y et al. | — | 2017 | → |
| CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits. | Macé A et al. | — | 2017 | → |
| Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants that contribute to lipid levels and coronary artery disease. | Lu X et al. | — | 2017 | → |
| Exome-wide association study of plasma lipids in >300,000 individuals. | Liu DJ et al. | — | 2017 | → |
| Exome-wide association study reveals novel psoriasis susceptibility locus at TNFSF15 and rare protective alleles in genes contributing to type I IFN signalling. | Dand N et al. | — | 2017 | → |
| Genetics of early-onset Parkinson's disease in Finland: exome sequencing and genome-wide association study. | Siitonen A et al. | — | 2017 | → |
| Heritability and GWAS Analyses of Acne in Australian Adolescent Twins. | Mina-Vargas A et al. | — | 2017 | → |
| Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease. | Zhao W et al. | — | 2017 | → |
| Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease. | Arneson D et al. | — | 2017 | → |
| PreMeta: a tool to facilitate meta-analysis of rare-variant associations. | Tang ZZ et al. | — | 2017 | → |
| Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies. | Benner C et al. | — | 2017 | → |
| Rare and low-frequency coding variants alter human adult height. | Marouli E et al. | — | 2017 | → |
| Whole exome analyses to examine the impact of rare variants on left ventricular traits in African American participants from the HyperGEN and GENOA studies. | Do AN et al. | — | 2017 | → |
| A pathway-centric approach to rare variant association analysis. | Richardson TG et al. | — | 2016 | → |
| A Protein Domain and Family Based Approach to Rare Variant Association Analysis. | Richardson TG et al. | — | 2016 | → |
| Coding-sequence variants are associated with blood lipid levels in 14,473 Chinese. | Lu X et al. | — | 2016 | → |
| Comparison of multiple single-nucleotide variant association tests in a meta-analysis of Genetic Analysis Workshop 19 family and unrelated data. | Wang S et al. | — | 2016 | → |
| Discovery of rare variants for complex phenotypes. | Kosmicki JA et al. | — | 2016 | → |
| Exome chip analyses in adult attention deficit hyperactivity disorder. | Zayats T et al. | — | 2016 | → |
| metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. | Cichonska A et al. | — | 2016 | → |
| Protective coding variants in CFH and PELI3 and a variant near CTRB1 are associated with age-related macular degeneration†. | Yu Y et al. | — | 2016 | → |
| RVTESTS: an efficient and comprehensive tool for rare variant association analysis using sequence data. | Zhan X et al. | — | 2016 | → |
| A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing. | Wang Q et al. | — | 2015 | → |
| Associating rare genetic variants with human diseases. | Zhang Q | — | 2015 | → |
| Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus. | Mahajan A et al. | — | 2015 | → |
| Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs. | Tang ZZ et al. | — | 2015 | → |
| Novel rare variations of the oxytocin receptor (OXTR) gene in autism spectrum disorder individuals. | Liu X et al. | — | 2015 | → |
| SEQMINER: An R-Package to Facilitate the Functional Interpretation of Sequence-Based Associations. | Zhan X et al. | — | 2015 | → |