Development of an exome pipeline for the identification of single nucleotide variants and indels from ovarian cancer tissue

Abstract: Approximately a quarter of a million women are diagnosed with ovarian cancer annually worldwide. Identifying the genes involved may ultimately lead to the development of corrective and preventive measures to fight this type of cancer. Next Generation Sequencing is a technology that can reveal the genes central to cancer initiation and development, however the analysis of the data is problematic due to the magnitude of information created and the diversity of the bioinformatic tools available. Here, a bioinformatic pipeline system was designed to test various components in their ability to process data collected from a rather rare, but aggressive type of ovarian cancer called ovarian clear-cell cancer. It was shown that this flexible modular-based pipeline system, which allowed for individual components to be easily compared, identified a single, optimal pipeline for the clear-cell data from a total of approximately 24 different pipeline combinations. This optimized pipeline was used to identify a set of genes from three patients that were associated with this disease, along with other mutations not currently recognized as cancer-related.