Standards > reporting guideline > bsg-s000174


ready Minimal Information about a high throuput SEQuencing Experiment

Abbreviation:MINSEQE


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General Information
MINSEQE describes the Minimum Information about a high-throughput nucleotide SEQuencing Experiment that is needed to enable the unambiguous interpretation and facilitate reproduction of the results of the experiment. By analogy to the MIAME guidelines for microarray experiments, adherence to the MINSEQE guidelines will improve integration of multiple experiments across different modalities, thereby maximising the value of high-throughput research.

Homepage http://fged.org/projects/minseqe/

Developed in Worldwide

Created in 2008

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Record updated: July 27, 2016, 2:48 p.m. by The BioSharing Team.




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ArrayExpress
ArrayExpress is a database of functional genomics experiments that can be queried and the data downloaded. It includes gene expression data from microarray and high throughput sequencing studies. Data is collected to MIAME and MINSEQE standards. Experiments are submitted directly to ArrayExpress or are imported from the NCBI GEO database.

Sequence Read Archive
The Sequence Read Archive (SRA) stores raw sequencing data from the next generation of sequencing platforms Data submitted to SRA. It is organized using a metadata model consisting of six objects: study, sample, experiment, run, analysis and submission. The SRA study contains high-level information including goals of the study and literature references, and may be linked to the INSDC BioProject database.

Genome Sequence Archive
GSA is a data repository specialized for archiving raw sequence reads. It supports data generated from a variety of sequencing platforms ranging from Sanger sequencing machines to single-cell sequencing machines and provides data storing and sharing services free of charge for worldwide scientific communities. In addition to raw sequencing data, GSA also accommodates secondary analyzed files in acceptable formats (like BAM, VCF). Its user-friendly web interfaces simplify data entry and submitted data are roughly organized as two parts, viz., Metadata and File, where the former can be further assorted into BioProject, BioSample, Experiment and Run, and the latter contains raw sequence reads.


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