Improving quality and reliability of results in gene expression studies by accounting for systematic artefacts

With the growing complexity and procurement costs of these high-throughput platforms, it is becoming increasingly common for the experiments to be deployed in central ‘core facilities’. This service-oriented paradigm is a recent development and one that is generally welcomed by lab-researchers and data-analysts as it encourages the standardisation of experimental protocols and reduces costs of hardware maintenance.

Despite the advances in manufacturing-quality, experimental efficiency, and overall reliability seen in these hardware platforms, certain issues regarding the accuracy of results gleamed from such experiments remain unresolved amongst those in the scientific community. Among those in question are high-throughput genome sequencing, gene microarrays, and quantitative polymerase chain reaction (qPCR) assays.

The main hypothesis is that the quality, and therefore also the reliability, of results gathered through gene-expression studies can be improved through careful management of the entire experimental workflow, rather than simply through optimisation of its individual steps.