Rapid Development and Distribution of Statistical Tools for High-Throughput Sequencing Data

WP2 Identifying Complex Genomic Variations

OBJECTIVES
Detecting genomic variants such as SNVs, copy number variations (CNVs) and structural variants (SVs) including insertions, deletions, gene fusions and translocations from whole-genome sequencing, RNA-Seq and exome-Seq, is currently one of the major applications of HTS. It is an essential component of understanding the association of genotypic difference with phenotypic consequences. Accurate detection of such variations is crucial in many areas of biology including association studies or cancer genomics. While many methods for genomic variation detection from HTS data have been proposed so far, there are two key problems. Firstly, they lack accuracy at low (< 5x) or medium (5x–20x) coverage which is the most cost-effective study design. Secondly, current methods call variants against the reference genome. However, a key challenge is comparative variant calling, for instance between related individuals or different samples from a single individual that have undergone somatic mutations (e.g. cancer). The objective of this work package is to develop and implement new tools for fast and accurate estimation of such complex genomic variations.

 

PARTICIPATING PARTNERS
ARMINES (Lead Partner)
Genomatix
University of Cambridge