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Published on: December 9, 2016
Computational identification of specific splicing regulatory elements from RNA-seq in lung cancer
1Department of Respiratory Medicine, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.
Background:
Lung cancer is the most common cause of cancer-related death worldwide. Recently, deep transcriptional sequencing has been used as an effective genomic assay to get an insight into this disease.
Aim:
This study is carried out to identify specific regulatory elements (SREs) in lung cancer.
Materials And Methods:
The RNA-sequencing data on lung cancer sample and normal sample were downloaded from NCBI. TopHat and Cufflinks were used to analyze differential alternative splicing in lung cancer by using RNA-sequencing data. Further, we searched specific SREs in lung cancer through finding over-represented hexamers around high expression exons.
Results:
According to the Jensen-Shannon divergence between two samples and the p-value of t-test, we found 53 genes with differential alternative splicing in lung cancer. In the analysis of SREs, we found 763 specific SREs between lung cancer sample and normal sample.
Conclusions:
These results may give an insight into how alternative splicing causes differential expression in lung cancer.
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