ArticleEuropean journal of human genetics : EJHG2011
Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies.
Article in European journal of human genetics : EJHG, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?Genetic epidemiology · 2016Pooled it
- A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes.European journal of human genetics : EJHG · 2014Pooled it
- SomamiR 2.0: a database of cancer somatic mutations altering microRNA-ceRNA interactions.Nucleic acids research · 2016Article
- Bioinformatics Resources for MicroRNA Discovery.Biomarker insights · 2015Review
- Incorporation of personal single nucleotide polymorphism (SNP) data into a national level electronic health record for disease risk assessment, part 1: an overview of requirements.JMIR medical informatics · 2014Article
- A review of cancer risk prediction models with genetic variants.Cancer informatics · 2014Review
- Phenotype-Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources.European journal of human genetics : EJHG · 2014Article
- Genetic variants in DNA repair pathway genes and risk of esophageal squamous cell carcinoma and gastric adenocarcinoma in a Chinese population.Carcinogenesis · 2013Article
- SomamiR: a database for somatic mutations impacting microRNA function in cancer.Nucleic acids research · 2013Article
- Article
- Genomics era and complex disorders: Implications of GWAS with special reference to coronary artery disease, type 2 diabetes mellitus, and cancers.Journal of postgraduate medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the field of cancer, genetic association studies are among the most active and well-funded research areas, and have produced hundreds of genetic associations, especially in the genome-wide association studies (GWAS) era. Knowledge synthesis of these discoveries is the first critical step in translating the rapidly emerging data from cancer genetic association research into potential applications for clinical practice. To facilitate the effort of translational research on cancer genetics, we have developed a continually updated database named Cancer Genome-wide Association and Meta Analyses database that contains key descriptive characteristics of each genetic association extracted from published GWAS and meta-analyses relevant to cancer risk. Here we describe the design and development of this tool with the aim of aiding the cancer research community to quickly obtain the current updated status in cancer genetic association studies.
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.