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.

RNASeq 数据的优点在很大程度上依赖于正确的标准化。然而，大多数方法假设大多数转录本在条件之间没有表现出差异表达。这一假设可能并不总是正确的，特别是当一种情况导致过度表达时。我们提出了一种新方法 (NormQ)，使用从 RT-qPCR 观察到的所选标记基因的相对比例来标准化 RNASeq 文库大小。使用模拟和真实数据集将该方法与流行的比率中值方法进行比较。 NormQ 为模拟数据集中的差异表达基因提供了更多匹配，并为模拟数据集和真实数据集提供了更多分布图匹配。