RNA-Seq, a deep sequencing technique, promises to be a potential successor to microarrays for studying the transcriptome. One of many aspects of transcriptomics that are of interest to researchers is gene expression estimation. With rapid development in RNA-Seq, there are numerous tools available to estimate gene expression, each producing different results. However, which of these tools produces the most accurate gene expression estimates in still unknown.
In this study researchers at the Georgia Institute of Technology, have addressed this issue using Cufflinks, IsoEM, HTSeq, and RSEM to quantify RNA-Seq expression profiles. Comparing results of these quantification tools, they observed that RNA-Seq relative expression estimates correlate with RT-qPCR measurements in the range of 0.85 to 0.89, with HTSeq exhibiting the highest correlation. But, in terms of root-mean-square deviation of RNA-Seq relative expression estimates from RT-qPCR measurements, they found HTSeq to produce the greatest deviation. Therefore, they conclude that, though Cufflinks, RSEM, and IsoEM might not correlate as well as HTSeq with RT-qPCR measurements, they may produce expression values with higher accuracy.
- Chandramohan R, Wu PY, Phan JH, Wang MD. (2013) Benchmarking RNA-Seq quantification tools. Conf Proc IEEE Eng Med Biol Soc 2013, 647-650. [abstract]