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- Title
MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive.
- Authors
Bernstein, Matthew N.; AnHai Doan; Dewey, Colin N.
- Abstract
Motivation: The NCBI's Sequence Read Archive (SRA) promises great biological insight if one could analyze the data in the aggregate; however, the data remain largely underutilized, in part, due to the poor structure of the metadata associated with each sample. The rules governing submissions to the SRA do not dictate a standardized set of terms that should be used to describe the biological samples from which the sequencing data are derived. As a result, the metadata include many synonyms, spelling variants and references to outside sources of information. Furthermore, manual annotation of the data remains intractable due to the large number of samples in the archive. For these reasons, it has been difficult to perform large-scale analyses that study the relationships between biomolecular processes and phenotype across diverse diseases, tissues and cell types present in the SRA. Results: We present MetaSRA, a database of normalized SRA human sample-specific metadata following a schema inspired by the metadata organization of the ENCODE project. This schema involves mapping samples to terms in biomedical ontologies, labeling each sample with a sampletype category, and extracting real-valued properties. We automated these tasks via a novel computational pipeline.
- Subjects
METADATA; AGGREGATED data; SYNONYMS; SEQUENCE (Linguistics); ENCODE Project
- Publication
Bioinformatics, 2017, Vol 33, Issue 18, p2914
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btx334