Utilizing HIVE: High-Performance Integrated Virtual Environment in Next-Generation High-Throughput Sequencing Analysis of mRNA in Schizophrenia.

Friday, November 08, 2013 — Poster Session III
10:00 a.m. – 12:00 p.m.	FAES Academic Center (Upper-Level Terrace)	FDA/CBER	GEN-25

Authors

O Muravitskaja
H Dingerdissen
R Mazumder
T Postolache
V Simonyan

Abstract

The rapid expansion of the next-generation sequencing (NGS) data has facilitated the development of the infrastructures capable of supporting the storage and analysis demands of genomics. High-performance Integrated Virtual Environment (HIVE) provides the infrastructure, algorithmics, user-friendly interfaces and tools for seamless and rapid NGS data processing, computation, analysis and storage. Utilizing this environment, enormous possibilities of discovery research in medicine arise. In this pilot study we replicated the results of Wu et al, 2012, using the HIVE-hexagon alignment, profiler and Sequence Blast algorithms. The objective of the study was to confirm the effectiveness of HIVE in producing reliable, cheap and quick analysis of RNA-Seq data before taking on larger scale discovery research in the field of psychiatry. We used publicly available 76bp RNA-Seq data reads of Wu et al, 2012. The data contained mRNA sequences of 9 schizophrenia male patients and 9 non-psychiatric controls, obtained in postmortem superior temporal gyrus (STG/BA22). The data was aligned to human transcriptome utilizing the HIVE-hexagon alignment and profiler algorithms. Here we demonstrate that applying HIVE to NGS data analysis holds a promising potential for expanding psychiatric research due to its ability to outcompete other industry tools to produce fast, reliable, accurate and reproducible analysis.