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A generic Transcriptomics Reporting Framework (TRF) for ‘omics data processing and analysis

Publication date: 

4 Nov 2017



Timothy W. Gant, Ursula G. Sauer, Shu-Dong Zhang, Brian N. Chorley, Jörg Hackermüller, Stefania Perdichizzi, Knut E. Tollefsen, Ben van Ravenzwaay, Carole Yauk, Weida Tong, Alan Poole.

Publication type: 



A generic Transcriptomics Reporting Framework (TRF) is presented that lists parameters that should be reported in ‘omics studies used in a regulatory context. The TRF encompasses the processes from transcriptome profiling from data generation to a processed list of differentially expressed genes (DEGs) ready for interpretation. Included within the TRF is a reference baseline analysis (RBA) that encompasses raw data selection; data normalisation; recognition of outliers; and statistical analysis. The TRF itself does not dictate the methodology for data processing, but deals with what should be reported. Its principles are also applicable to sequencing data and other ‘omics. In contrast, the RBA specifies a simple data processing and analysis methodology that is designed to provide a comparison point for other approaches and is exemplified here by a case study. By providing transparency on the steps applied during ‘omics data processing and analysis, the TRF will increase confidence processing of ‘omics data, and regulatory use. Applicability of the TRF is ensured by its simplicity and generality. The TRF can be applied to all types of regulatory ‘omics studies, and it can be executed using different commonly available software tools