ArticleBMC bioinformatics2014
The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- EGAsubmitter: A software to automate submission of nucleic acid sequencing data to the European Genome-phenome Archive.Frontiers in bioinformatics · 2023Article
- pISA-tree - a data management framework for life science research projects using a standardised directory tree.Scientific data · 2022Article
- Article
- isa4j: a scalable Java library for creating ISA-Tab metadata.F1000Research · 2020Article
- PhenoMeNal: processing and analysis of metabolomics data in the cloud.GigaScience · 2019Article
- mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data.Bioinformatics (Oxford, England) · 2017Article
- The Ontology for Biomedical Investigations.PloS one · 2016Article
- Data standards can boost metabolomics research, and if there is a will, there is a way.Metabolomics : Official journal of the Metabolomic Society · 2016Review
- From Peer-Reviewed to Peer-Reproduced in Scholarly Publishing: The Complementary Roles of Data Models and Workflows in Bioinformatics.PloS one · 2015Article
- NETTAB 2012 on "Integrated Bio-Search".BMC bioinformatics · 2014Article
- MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.Frontiers in bioengineering and biotechnology · 2014Article
- linkedISA: semantic representation of ISA-Tab experimental metadata.BMC bioinformatics · 2014Article
- COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access.Metabolomics : Official journal of the Metabolomic SocietyArticle
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
backgroundThe ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. To attract further interest towards the format and extend support to ensure reproducible research and reusable data, we present the Risa package, which delivers a central component to support the ISA format by enabling effortless integration with R, the popular, open source data crunching environment.
resultsThe Risa package bridges the gap between the metadata collection and curation in an ISA-compliant way and the data analysis using the widely used statistical computing environment R. The package offers functionality for: i) parsing ISA-Tab datasets into R objects, ii) augmenting annotation with extra metadata not explicitly stated in the ISA syntax; iii) interfacing with domain specific R packages iv) suggesting potentially useful R packages available in Bioconductor for subsequent processing of the experimental data described in the ISA format; and finally v) saving back to ISA-Tab files augmented with analysis specific metadata from R. We demonstrate these features by presenting use cases for mass spectrometry data and DNA microarray data.
conclusionsThe Risa package is open source (with LGPL license) and freely available through Bioconductor. By making Risa available, we aim to facilitate the task of processing experimental data, encouraging a uniform representation of experimental information and results while delivering tools for ensuring traceability and provenance tracking. SOFTWARE AVAILABILITY: The Risa package is available since Bioconductor 2.11 (version 1.0.0) and version 1.2.1 appeared in Bioconductor 2.12, both along with documentation and examples. The latest version of the code is at the development branch in Bioconductor and can also be accessed from GitHub https://github.com/ISA-tools/Risa, where the issue tracker allows users to report bugs or feature requests.
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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.