Big Data to Knowledge: Common Pitfalls in Transcriptomics Data Analysis and Representation Publisher Pubmed



Abedi M^{1, 2} ; Fatehi R² ; Moradzadeh K² ; Gheisari Y^{1, 2} Show Affiliations
Source: RNA Biology Published:2019

Abstract

The omics technologies provide an invaluable opportunity to employ a global view towards human diseases. However, the appropriate translation of big data to knowledge remains a major challenge. In this study, we have performed quality control assessments for 91 transcriptomics datasets deposited in gene expression omnibus database and also have evaluated the publications derived from these datasets. This survey shows that drawbacks in the analyses and reports of transcriptomics studies are more common than one may assume. This report is concluded with some suggestions for researchers and reviewers to enhance the minimal requirements for gene expression data generation, analysis and report. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.