RNA-seq 定量軟體之比較

Abstract

RNA-seq是最近廣泛使用於轉錄體學的工具。藉由高通量定序科技，能達到更精確的基因表現量測定。然而，RNA-seq的定量結果可能因為生物特性或是實驗流程而有所偏差，近年來研究者們針對偏差校正開發出許多定量軟體，本篇論文主要目的即是比較RSEM、Cufflinks、IsoEM、Genominator、以及RNASeqBias等五種軟體的優劣。我們採用軟體所跑出的表現量取對數值和Taqman qRT-PCR對數表現量值的spearman相關係數來評判。根據mapping的結果顯示，我們使用的MAQC人腦樣本有長度偏差的問題。除了使用MAQC計畫中的Taqman qRT-PCR做為定量表現的基準外，我們也評估各軟體在偏差校正上的效果。分析成果指出五種軟體皆能夠達到長度效應的校正。另外，雖然Cufflinks、IsoEM、Genominator、和RNASeqBias都具有校正sequence-specific偏差的功能，但只有Cufflinks稍微較明顯能減緩此效應。整體來說，Cufflinks在RNA-seq資料上具有最好的校正效果與表現。

RNA-seq is a more accurate technology in measuring transcripts levels by using high-throughput sequencing of cDNA. However, the quantification of mRNA abundances from RNA-seq data may be biased due to various biological or statistical effects. Several RNA-seq quantification software, including RSEM, Cufflinks, IsoEM, Genominator, and RNASeqBias, had been recently proposed to correct such biases. The objective of this study was to compare the above five software by applying RNA-seq analysis to a benchmark MAQC human brain data while the Taqman qRT-PCR dataset was treated as the golden-standard to evaluate them. Different software was compared to each other based on their associations between the log expression values that obtained from each method and the Taqman log value. In addition, we also discussed the level of biases correction for the programs. According to the mapping results, it was observed that the transcript length effects did exist in the MAQC data. The analytic results showed that all software can reduce length biases. Although Cufflinks, IsoEM, Genominator, and RNASeqBias have the functions to correct sequence-specific biases, only Cufflinks has a bit apparent to correct sequence-specific biases. In conclusion, Cufflinks has the best performance in biases correction for RNA-seq data.