In order to solve the problem of early differential diagnosis of ovarian cancer, this paper proposes the role of bioinformatics analysis in early differential diagnosis of ovarian cancer. This method uses bioinformatics methods to mine the existing data in the tumor database and obtain tumor-related molecules. It is an efficient method to obtain effective biomarkers, screen signal pathway molecules, and reveal the internal mechanism of tumor occurrence and development. Using this method can greatly improve the efficiency and reliability of screening diagnosis, prognosis, and treatment targets. The results showed that 5821 new lncRNA transcripts and 4611 new lncRNA genes were identified by lncScore from the assembled transcripts. 10 new lncRNA transcripts and 174 new lncRNA genes were found to be differentially expressed in ovarian cancer.