By sequencing technologies it is possible to “read” a DNA molecule, that is determine the precise order of its nucleotides. A DNA molecule cannot be read from the beginning to the end like a book: it has to be fragmented in small pieces which are sequenced separately and then combined together by computational algorithms like a puzzle. The high demand for low cost sequencing has driven the development of high-throughput or “second generation” sequencing technologies, able to parallelize sequencing process by producing millions of DNA sequences at once. Sequencers alone, however, are not enough to explain the possible genomic variability underlying diseases, behaviours and traits of living beings. Moreover, the quantity of data generated by these machines is huge (order of TeraBytes per week with a single sequencer).  

Bioinformatics here aims to manage, handle and interpret sequencing data in order to identify or suggest correlations between genomic patterns and one or more phenotypes of interest.

Specifically, in our laboratory we are active and we have know how on:

• data analysis on the main sequencing platforms on the market: Illumina (GA, HiSeq, MiSeq) and Life Technologies (Solid, Ion Torrent, Ion Proton);

• set up and management of the data analysis environments on high performance, cluster and cloud computing;

• optimization of data analysis pipelines for a high-automated and high-parallel processing;

•  design and implementation of analysis pipelines for the following sequencing applications: whole-genome, targeted resequencing (genes panel, amplicons, whole-exome), RNA-seq and Cancer-seq;

• publicly genomic databases and design of ad-hoc genomic data resources;

• development of new methodologies, algorithms and procedures needed by the different applications in order to increase power and improve the quality of results.