Kristen is currently a student in the University of Sydney mathematics department. He has completed a Bachelor of Science (Advanced Mathematics) with a major in statistics. He is currently interested in researching multiple hypothesis testing in a biological setting, or more specifically, examining and controlling the false discovery rate of multiple tests in order to minimise error.
When matching fragmentation spectrum generated in an MS/MS experiment to a database of peptides one encounters a massive multiple testing problem. The standard way to deal with this problem is through the control of the FDR. More recently scientists became interested in identifying matches to less commonly found peptide variants which means the searched database have become significantly larger. In order to avoid loss of power when searching the more commonly found variants a nested search was proposed, where peptide databases are searched in the order of their relevance. We will look into how one can rigorously control the FDR when employing such a sequential search protocol.