Abstract

This work regards the use of high performance computing (HPC) methods for a new bioinformatics challenge: the analysis of Terabyte-size data generated by the new ultra high throughput sequencing (UHTS) technology. As in microarray or mass spectrometry cases, public repositories are growing to store data from the next generation studies produced in laboratories around the world. These can be used to access to a large number of samples from experiments with different individuals, populations and sequencing platforms. Also experimental data of scientific articles are published in these stores, enabling to repeat and verify their results (reproducibility). An automatic downloader and analyzer system (D-Daemons architecture) is proposed to interface to a public repository of sequence reads, select all the experiments that match some research parameters, defined by a user, download them and apply an analysis pipeline to evidence their similarity or variability. A software pipeline based on this architecture and operating in a HPC environment has been developed to analyze the downloaded UHTS files in the shortest time possible. A case study of the system on “Colorectal Cancer (CRC) cell line” datasets and an aligner selection in a SNP discovery task on three RNA-Seq datasets (Human Breast tissue and of BT474 & MCF7 cell lines) are presented.