Dr Felicity Newell
Queensland University of Technology
The first step that is often required to analyse next generation sequencing data is to align the reads that are generated to a reference genome. Current sequencing platforms can generate high volumes of raw read data. Such reads are usually short in length and may contain sequencing errors. Therefore tools that perform mapping need to be able to efficiently identify the location of a read within the reference genome while accounting for real sequence variations as well as technical artefacts. In this presentation I will describe some of the approaches to sequence alignment, highlighting some of the popular tools that are in use. A good understanding of the common errors and biases that can occur with mapping is necessary in order to obtain high quality data from downstream analyses such as variant detection. I will also discuss some of these errors and outline some quality controls steps that can be performed.
Felicity Newell originally trained in the fields of molecular and cellular biology, and received her PhD from The University of Queensland in 2007. Following this, she completed a Master of Information Technology at the Queensland University of Technology. She has worked as a bioinformatics programmer, developing biological web applications at QFAB and software for the analysis of cancer sequencing data at the Queensland Centre for Medical Genomics at UQ. Since then, she has conducted postdoctoral research at The University of Queensland Diamantina Institute, and this year she joined QUT as a Research Fellow in Computational Biology. Her current interests involve using next generation sequencing data to investigate the genetics of autoimmune diseases and cancer.