ArticleAnnual review of statistics and its application2016
Statistical Methods in Integrative Genomics.
Article in Annual review of statistics and its application, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 2 of them syntheses 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
59 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Molecular profiling of coronary stent testenosis: A systematic review and functional analysis of implicated genes.Medicine · 2026Pooled it
- Statistical genomics in rare cancer.Seminars in cancer biology · 2020Pooled it
- A three-groups non-local model for combining heterogeneous data sources to identify genes associated with Parkinson's disease.Biometrics · 2026Article
- Dynamic Factor Analysis for Sparse and Irregular Longitudinal Data: An Application to Metabolite Measurements in a COVID-19 Study.Statistics in medicine · 2026Article
- A fast integrative clustering and feature selection approach for high-dimensional multiview data.Statistical methods in medical research · 2026Article
- Hierarchical structure-guided high-dimensional multi-view clustering.Journal of multivariate analysis · 2026Article
- Genetic architecture and analysis practices of circulating metabolites in the NHLBI Trans-Omics for Precision Medicine Program.American journal of human genetics · 2025Article
- Roadblocks of Urinary EV Biomarkers: Moving Toward the Clinic.Journal of extracellular vesicles · 2025Review
- Rank Aggregation Methods and Tools in Genomic Data Analysis.Current genomics · 2025Review
- The role of double heterozygotes of SLC3A1 and SLC7A9 in the prevalence of cystine stones.Genetics in medicine : official journal of the American College of Medical Genetics · 2025Article
- Heterogeneity-aware integrative regression for ancestry-specific association studies.Biometrics · 2024Article
- A model-free and distribution-free multi-omics integration approach for detecting novel lung adenocarcinoma genes.Scientific reports · 2024Article
- NetMIM: network-based multi-omics integration with block missingness for biomarker selection and disease outcome prediction.Briefings in bioinformatics · 2024Article
- Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.Journal of the American Statistical Association · 2024Article
- Mediation Analysis for High-Dimensional Mediators and Outcomes with an Application to Multimodal Imaging Data.Computational statistics & data analysis · 2023Article
- Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges.BMC medicine · 2023Review
- Generalized Liquid Association Analysis for Multimodal Data Integration.Journal of the American Statistical Association · 2023Article
- Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis.Journal of the American Statistical Association · 2023Article
- Article
- An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types.PLOS digital health · 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
3 authors.
Funding
Abstract
Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions.
Indexed as
Identifiers
What OpenQuestion holds
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.