摘要
The emerging RNA-Seq technology makes it possible to infer splicing variants from millions of short sequence reads. Here we present a method to identify isoforms by their specific signatures on chromosomes including both exons and junctions. By applying this method to a RNA-Seq dataset of gastric cancer, we showed that our method is more accurate and sensitive than other isoform inference tools such as RSEM and Cufflinks. By constructing a network from gene list identified by our method but missed by other tools, we found that some cancer-related genes enriched in network modules have significant implications for cancer drug discovery.
The emerging RNA-Seq technology makes it possible to infer splicing variants from millions of short sequence reads. Here we present a method to identify isoforms by their specific signatures on chromosomes including both exons and junctions. By applying this method to a RNA-Seq dataset of gastric cancer, we showed that our method is more accurate and sensitive than other isoform inference tools such as RSEM and Cufflinks. By constructing a network from gene list identified by our method but missed by other tools, we found that some cancer-related genes enriched in network modules have significant implications for cancer drug discovery.
