standards > reporting guideline > DOI:10.25504/FAIRsharing.vy4h4j


ready Minimal Information for QTLs and Association Studies

Abbreviation: MIQAS


General Information
The MIQAS set of rules accompanied with the standardized XML and tab-delimited file formats will serve two goals: to encourage research groups that wish to publish a QTL paper to provide and submit the necessary information that would make meta-analysis possible. to allow easy interchange of data between different QTL and association analysis databases. Databases that implement the standardized XML format will typically write an import and an export filter to read data from and dump data into that an XML file.

Homepage http://miqas.sourceforge.net/

Countries that developed this resource United Kingdom , United States

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How to cite this record FAIRsharing.org: MIQAS; Minimal Information for QTLs and Association Studies; DOI: https://doi.org/10.25504/FAIRsharing.vy4h4j; Last edited: Jan. 8, 2019, 1:34 p.m.; Last accessed: Aug 21 2019 11:05 a.m.


Record updated: Oct. 16, 2016, 9:58 p.m. by The FAIRsharing Team.

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In Collections
Minimum Information for Biological and Biomedical Investigations


Support

General

online documentation http://mibbi.sf.net/projects/MIQAS.shtml

Additional Information

Contact Jan Aerts   ORCID


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Related Standards

Reporting Guidelines

No guidelines defined

Terminology Artifacts

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Models and Formats

Identifier Schemas

No identifier schema standards defined

Metrics

No metrics standards defined


Implementing Databases (1)
Animal Quantitative Trait Loci (QTL) Database
The Animal Quantitative Trait Loci (QTL) Database (Animal QTLdb) strives to collect all publicly available trait mapping data, i.e. QTL (phenotype/expression, eQTL), candidate gene and association data (GWAS), and copy number variations (CNV) mapped to livestock animal genomes, in order to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features such as annotated genes.

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