Document Type
Journal Article
Publication Date
2013
Journal
Journal of Metabolomics and Systems Biology
Volume
Volume 1, Issue 1
Inclusive Pages
Article number 7
Abstract
Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNP-centered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets.
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
APA Citation
Mudvari, P., Kowsari, K., Cole, C., Mazumder, R., Horvath, A. (2013). Extraction of molecular features through exome to transcriptome alignment. Journal of Metabolomics and Systems Biology, 1(1):7.
Peer Reviewed
1
Open Access
1
Comments
Reproduced with permission of Avens Publishing Group, Journal of Metabolomics & Systems Biology.