1 Section for Plant Biochemistry, Department of Plant and Environmental Sciences, Faculty of Science, Københavns Universitet2 University of Tennessee, Knoxville3 Aarhus University4 Institut for Molekylærbiologi og Genetik - Afgrødegenetik og Bioteknologi5 Section for Plant Biochemistry, Department of Plant and Environmental Sciences, Faculty of Science, Københavns Universitet6 University of Tennessee, Knoxville
performance-dependency on inter-replicate and inter-treatment biases
This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies. For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies of correction methods are influenced by the inter-treatment bias as well as the inter-replicate variance. Therefore, we recommend inspecting both of the bias sources in order to apply the most efficient correction method. As an alternative correction strategy, sequential application of different correction approaches is also advised.
Journal of Biotechnology, 2014, Vol 188, p. 100-109
Data correction; Gene expression; Inter-replicate bias; Inter-treatment biasa; Inter-treatment bias