Literature DB >> 24518066

Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS).

Uma D Vempati1, Caty Chung1, Chris Mader1, Amar Koleti1, Nakul Datar1, Dušica Vidović1, David Wrobel2, Sean Erickson2, Jeremy L Muhlich3, Gabriel Berriz3, Cyril H Benes4, Aravind Subramanian5, Ajay Pillai6, Caroline E Shamu7, Stephan C Schürer8.   

Abstract

The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.
© 2014 Society for Laboratory Automation and Screening.

Entities:  

Keywords:  cell-based assays; data standards; database and data management; enzyme assays or enzyme kinetics; gene expression; metadata

Mesh:

Substances:

Year:  2014        PMID: 24518066      PMCID: PMC7723305          DOI: 10.1177/1087057114522514

Source DB:  PubMed          Journal:  J Biomol Screen        ISSN: 1087-0571


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