Computational identification of specific splicing regulatory elements from RNA-seq in lung cancer.
Eur Rev Med Pharmacol Sci
; 17(13): 1716-21, 2013 Jul.
Article
en En
| MEDLINE
| ID: mdl-23852893
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 ANDMETHODS:
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.
Buscar en Google
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
ARN Neoplásico
/
Empalme del ARN
/
Elementos Reguladores de la Transcripción
/
Neoplasias Pulmonares
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Eur Rev Med Pharmacol Sci
Asunto de la revista:
FARMACOLOGIA
/
TOXICOLOGIA
Año:
2013
Tipo del documento:
Article
País de afiliación:
China