Statistical analysis of trapped-ion-mobility time-of-flight mass spectrometry proteomics data

Statistical analysis of trapped-ion-mobility time-of-flight mass spectrometry proteomics data

Project details

This project is a collaboration between Professor Smyth's lab, which specialises in statistical bioinformatics, and the Institute's Proteomics Lab lead by Associate Professor Webb. The Institute has recently become an early adopter of the new trapped-ion-mobility time-of-flight (timsTOF) mass spectrometry technology. The new technology has the potential to speed data acquisition up to five times and produces an extra dimension of raw data in the form of collisional cross-sectional area, potentially increasing the resolution with which peptides can be identified.

The project will suit a student with high level expertise in statistics and computing. The project will focus on downstream statistical analysis issues, including normalisation, differential expression and treatment of missing values, but the opportunity also exists for making input into low-level data processing of the timsTOF data including detection and quantification of peptides.

About our research group

Professor Smyth's research lab has a history of developing new statistical techniques for the analysis of genomic data that are widely used or have become accepted international standards. Members the group typically have backgrounds in mathematics, statistics, computer science, genetics, engineering or physics. The group’s research has made particular use, for example, of empirical Bayes and generalised linear model techniques and has given particular attention to the analysis of complex genomic experiments involving multiple treatment factors. The group has developed a number of well-known software packages including limma, edgeR, goseq, Rsubread, csaw and diffHic, goseq.


Professor Gordon Smyth

Professor Gordon Smyth writing on a whiteboard
Joint Division Head

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