Methods and Strategies for Incorporating Data from the Latest Sequencing Platforms in Genomic Analyses

Over the last half decade, DNA sequencing technologies have improved by leaps and bounds. Currently, in all areas of biology we are inundated with sequencing data generated from many different technical platforms. In addition to the various platforms, every type of analysis performed on these sequence data can be approached using multiple bioinformatics tools. Hence it is important to understand the technical characteristics and limitations of each the sequencing platforms, as well as the bioinformatics tools, so that the right combination can be used for a given experiment. It is also crucial to design experiments to suit these methodologies so that the most accurate biological inference can be drawn. Finally, it is essential to understand the computational requirements (storage and processing capacity) and to identify appropriate resources prior to obtaining the data and starting the bioinformatics analysis.

We will be discussing a few examples of strategies that can be used to make sure that the experimental design is appropriate, given the biological question and the resources available. We will also discuss a few examples of the process involved in picking the best tool for a given analysis. In addition, in the context of these examples, we will highlight the various junctures during the bioinformatics analysis process at which quality checks can and should be performed.