ReviewAmerican journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics2015
Gene set analysis: A step-by-step guide.
Review in American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
What it found
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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.
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Who cites it
49 citing papers in PubMed.
- Genotype-environment correlation by intervention effects underlying middle childhood peer rejection and associations with adolescent marijuana use.Development and psychopathology · 2022Trial
- Gene set enrichment analysis to create polygenic scores: a developmental examination of aggression.Translational psychiatry · 2019Trial
- scGeneBank: cross-species screening of functional gene sets at single-cell resolution.Nucleic acids research · 2026Article
- Pseudotimecascade Visualizes Gene Expression Cascade in Pseudotime Analysis.Computational and structural biotechnology journal · 2026Article
- A practical guide to functional enrichment analysis.Frontiers in bioinformatics · 2026Article
- Unlocking the genetic code: a comprehensive Genome-Wide association study and gene set enrichment analysis of cell-mediated immunity in chickens.BMC genomics · 2025Article
- RNA-Seq and Gene Set Enrichment Analysis (GSEA) in Peripheral Blood Mononuclear Cells (PBMCs).Methods in molecular biology (Clifton, N.J.) · 2025Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Nucleocytoplasmic β-catenin expression contributes to neuroendocrine differentiation in muscle invasive bladder cancer.Cancer science · 2024Article
- Network enrichment significance testing in brain-phenotype association studies.Human brain mapping · 2024Article
- A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms.Biology · 2024Article
- Multi-omics and pathway analyses of genome-wide associations implicate regulation and immunity in verbal declarative memory performance.Alzheimer's research & therapy · 2024Article
- In Silico Models to Validate Novel Blood-Based Biomarkers.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Translation of genome-wide association study: from genomic signals to biological insights.Frontiers in genetics · 2024Review
- Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis.Molecular neurobiology · 2023Article
- Identification of candidate genes and pathways associated with juvenile idiopathic arthritis by integrative transcriptome-wide association studies and mRNA expression profiles.Arthritis research & therapy · 2023Article
- Using Recurrent Neural Networks for Predicting Type-2 Diabetes from Genomic and Tabular Data.Diagnostics (Basel, Switzerland) · 2022Article
- Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis.Journal of personalized medicine · 2022Review
- An overview of technologies for MS-based proteomics-centric multi-omics.Expert review of proteomics · 2022Article
- Kalpra: A kernel approach for longitudinal pathway regression analysis integrating network information with an application to the longitudinal PsyCourse Study.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
To maximize the potential of genome-wide association studies, many researchers are performing secondary analyses to identify sets of genes jointly associated with the trait of interest. Although methods for gene-set analyses (GSA), also called pathway analyses, have been around for more than a decade, the field is still evolving. There are numerous algorithms available for testing the cumulative effect of multiple SNPs, yet no real consensus in the field about the best way to perform a GSA. This paper provides an overview of the factors that can affect the results of a GSA, the lessons learned from past studies, and suggestions for how to make analysis choices that are most appropriate for different types of data. © 2015 Wiley Periodicals, Inc.
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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.