ArticleBioinformatics (Oxford, England)2013
A self-updating road map of The Cancer Genome Atlas.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed.
- B-CAN: a resource sharing platform to improve the operation, visualization and integrated analysis of TCGA breast cancer data.Oncotarget · 2017Article
- Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams.Briefings in bioinformatics · 2017Article
- Article
- Using Pharmacogenomic Databases for Discovering Patient-Target Genes and Small Molecule Candidates to Cancer Therapy.Frontiers in pharmacology · 2016Review
- Big data in medical science--a biostatistical view.Deutsches Arzteblatt international · 2015Review
- Human cancer databases (review).Oncology reports · 2015Review
- Comparison of targeted next-generation sequencing and Sanger sequencing for the detection of PIK3CA mutations in breast cancer.BMC clinical pathology · 2015Article
- Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks. Contribution of the IMIA Primary Healthcare Working Group.Yearbook of medical informatics · 2014Review
- QMachine: commodity supercomputing in web browsers.BMC bioinformatics · 2014Article
- TCGA-assembler: open-source software for retrieving and processing TCGA data.Nature methods · 2014Article
- Unique molecular signatures as a hallmark of patients with metastatic breast cancer: implications for current treatment paradigms.Oncotarget · 2014Article
- Genome and cancer single nucleotide polymorphisms of the human NEIL1 DNA glycosylase: activity, structure, and the effect of editing.DNA repair · 2014Article
- Navigating the multilayered organization of eukaryotic signaling: a new trend in data integration.PLoS computational biology · 2014Review
- Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data.BMC bioinformatics · 2014Article
- TopFed: TCGA tailored federated query processing and linking to LOD.Journal of biomedical semantics · 2014Article
- Mining genome sequencing data to identify the genomic features linked to breast cancer histopathology.Journal of pathology informatics · 2014Article
- RTCGAToolbox: a new tool for exporting TCGA Firehose data.PloS one · 2014Article
- OpenHealth Platform for Interactive Contextualization of Population Health Open Data.AMIA ... Annual Symposium proceedings. AMIA SymposiumArticle
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
motivationSince 2011, The Cancer Genome Atlas' (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months.
resultsWe developed an engine to index and annotate the TCGA files, relying exclusively on third-generation web technologies (Web 3.0). Specifically, this engine uses JavaScript in conjunction with the World Wide Web Consortium's (W3C) Resource Description Framework (RDF), and SPARQL, the query language for RDF, to capture metadata of files in the TCGA open-access HTTP directory. The resulting index may be queried using SPARQL, and enables file-level provenance annotations as well as discovery of arbitrary subsets of files, based on their metadata, using web standard languages. In turn, these abilities enhance the reproducibility and distribution of novel results delivered as elements of a web-based computational ecosystem. The development of the TCGA Roadmap engine was found to provide specific clues about how biomedical big data initiatives should be exposed as public resources for exploratory analysis, data mining and reproducible research. These specific design elements align with the concept of knowledge reengineering and represent a sharp departure from top-down approaches in grid initiatives such as CaBIG. They also present a much more interoperable and reproducible alternative to the still pervasive use of data portals. AVAILABILITY: A prepared dashboard, including links to source code and a SPARQL endpoint, is available at http://bit.ly/TCGARoadmap. A video tutorial is available at http://bit.ly/TCGARoadmapTutorial. CONTACT: robbinsd@uab.edu.
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.