Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville 3052, Australia.
Genome Biol. 2010;11(2):R14. doi: 10.1186/gb-2010-11-2-r14. Epub 2010 Feb 4.
We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. Application of GOseq to a prostate cancer data set shows that GOseq dramatically changes the results, highlighting categories more consistent with the known biology.
我们介绍了 GOseq，这是一款用于对 RNA-seq 数据进行基因本体论（GO）分析的应用程序。GO 分析被广泛用于减少全基因组表达研究中的复杂性并突出生物过程，但由于对长且高度表达的转录本的差异表达过度检测，标准方法在 RNA-seq 数据上产生有偏的结果。GOseq 在前列腺癌数据集上的应用表明，GOseq 极大地改变了结果，突出了更符合已知生物学的类别。
