ArticleBioinformatics (Oxford, England)2018
Meta-analytic principal component analysis in integrative omics application.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 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
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A new CCCH-type zinc finger-related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma patients.Frontiers in genetics · 2022Pooled it
- A Tutorial on Bayesian Multi-Study Factor Analysis With Applications in Nutrition and Genomics.Statistics in medicine · 2026Article
- Comparative study of the effects of baicalin and probenecid on microRNA expression profiles in porcine aortic vascular endothelial cells infected by Glaesserella parasuis.BMC veterinary research · 2025Article
- Identification of a C2H2 zinc finger-related lncRNA prognostic signature and its association with the immune microenvironment in clear cell renal cell carcinoma.Translational andrology and urology · 2025Article
- Construction and validation of immunogenic cell death-related molecular clusters, signature, and immune landscape in pancreatic cancer.Clinical and experimental medicine · 2024Article
- Principal component analysis revisited: fast multitrait genetic evaluations with smooth convergence.G3 (Bethesda, Md.) · 2024Article
- Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data.World journal of clinical oncology · 2024Article
- Article
- Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.Frontiers in molecular biosciences · 2024Review
- Batch-effect correction in single-cell RNA sequencing data using JIVE.Bioinformatics advances · 2024Article
- Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide.Frontiers in cell and developmental biology · 2024Review
- High-throughput sequencing reveals the change of TCR α chain CDR3 with Takayasu arteritis.Immunity, inflammation and disease · 2023Article
- Integrated single-cell and bulk RNA sequencing analysis identified pyroptosis-related signature for diagnosis and prognosis in osteoarthritis.Scientific reports · 2023Article
- Analysis of cuproptosis-related lncRNA signature for predicting prognosis and tumor immune microenvironment in pancreatic cancer.Apoptosis : an international journal on programmed cell death · 2023Article
- Identification of N7-methylguanosine-related lncRNAs for the risk stratification of hepatocellular carcinoma.Journal of gastrointestinal oncology · 2023Article
- Single cell RNA sequencing reveals mesenchymal heterogeneity and critical functions ofWorld journal of stem cells · 2023Article
- Identification and validation of fatty acid metabolism-related lncRNA signatures as a novel prognostic model for clear cell renal cell carcinoma.Scientific reports · 2023Article
- Single-cell RNA sequencing analysis of human chondrocytes reveals cell-cell communication alterations mediated by interactive signaling pathways in osteoarthritis.Frontiers in cell and developmental biology · 2023Article
- A multifaceted and feasible prognostic model of amino acid metabolism-related genes in the immune response and tumor microenvironment of head and neck squamous cell carcinomas.Frontiers in oncology · 2022Article
- Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.Frontiers in genetics · 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
5 authors.
Funding
Abstract
Motivation: With the prevalent usage of microarray and massively parallel sequencing, numerous high-throughput omics datasets have become available in the public domain. Integrating abundant information among omics datasets is critical to elucidate biological mechanisms. Due to the high-dimensional nature of the data, methods such as principal component analysis (PCA) have been widely applied, aiming at effective dimension reduction and exploratory visualization. Results: In this article, we combine multiple omics datasets of identical or similar biological hypothesis and introduce two variations of meta-analytic framework of PCA, namely MetaPCA. Regularization is further incorporated to facilitate sparse feature selection in MetaPCA. We apply MetaPCA and sparse MetaPCA to simulations, three transcriptomic meta-analysis studies in yeast cell cycle, prostate cancer, mouse metabolism and a TCGA pan-cancer methylation study. The result shows improved accuracy, robustness and exploratory visualization of the proposed framework. Availability and implementation: An R package MetaPCA is available online. (http://tsenglab.biostat.pitt.edu/software.htm). Contact: ctseng@pitt.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
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.