A framework for Alternative Splicing Isoforms Detection in Lung Cancer

Among all malignancies, Lung cancer (LC) is the dominant source of death which occupying the most frequent tumor worldwide. Accumulated mutations in individual genes leading to the initiation of lung cancer. One of these mutations results from post-transcription modification of messenger RNA (mRNA) which is played a pivotal role in mRNA maturity. Alternative splicing (AS) is one of the main approaches in detecting mRNA post-processing, where is proposed to be the main determinant for the generation of various transcriptional variants within a single gene. Usually, there are several methods for the identification and quantifications of AS from RNA-seq data; isoform-based (IS), exon-based (EX), and event-based (EV), each of these methods relies on a different method for AS detection. Here, IS approach has been used for our analysis, which provides more biological interpretation as it relies on detecting the associated transcripts or isoforms within a single gene. Interestingly, our analysis is not only detecting the genes correlated with lung cancer but also the different associated isoforms. Moreover, many potential LC biomarkers have been identified by our analysis, were strongly correlated with LC initiation, propagation, and metastasis.