The merit of RNASeq data relies heavily on correct normalization. However, most methods assume that the majority of transcripts show no differential expression between conditions. This assumption may not always be correct, especially when one condition results in overexpression. We present a new method (NormQ) to normalize the RNASeq library size, using the relative proportion observed from RT-qPCR of selected marker genes. The method was compared against the popular median-of-ratios method, using simulated and real-datasets. NormQ produced more matches to differentially expressed genes in the simulated dataset and more distribution profile matches for both simulated and real datasets.

Department of Cell Biology Faculty of Science Charles University Prague Czech Republic

Laboratory of Gene Expression Institute of Biotechnology of the Czech Academy of Sciences BIOCEV Prumyslova 595 Vestec 252 50 Czech Republic

University of South Bohemia in Ceske Budejovice Faculty of Fisheries and Protection of Waters South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses Research Institute of Fish Culture and Hydrobiology Vodnany Czech Republic

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