Literature DB >> 23852893

Computational identification of specific splicing regulatory elements from RNA-seq in lung cancer.

R-L Chen1, W Guo, Y Shi, H Wu, J Wang, G Sun.   

Abstract

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.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23852893

Source DB:  PubMed          Journal:  Eur Rev Med Pharmacol Sci        ISSN: 1128-3602            Impact factor:   3.507


  1 in total

1.  Graphical neuroimaging informatics: application to Alzheimer's disease.

Authors:  John Darrell Van Horn; Ian Bowman; Shantanu H Joshi; Vaughan Greer
Journal:  Brain Imaging Behav       Date:  2014-06       Impact factor: 3.978

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.