[show abstract][hide abstract] ABSTRACT: Imaging Mass Spectrometry (IMS) provides a means to measure the spatial distribution of biochemical features on the surface of a sectioned tissue sample. IMS datasets are typically huge and visualisation and subsequent analysis can be challenging. Principal component analysis (PCA) is one popular data reduction technique that has been used and we propose another; the minimum noise fraction (MNF) transform which is popular in remote sensing.
The MNF transform is able to extract spatially coherent information from IMS data. The MNF transform is implemented through an R-package which is available together with example data from http://staﬀ.scm.uws.edu.au/∼glenn/∖#Software.
In our example, the MNF transform was able to find additional images of interest. The extracted information forms a useful basis for subsequent analyses.
[show abstract][hide abstract] ABSTRACT: Aligment of mass spectrometry (MS) chromatograms is sometimes required prior to sample comparison and data analysis. Without alignment, direct comparison of chromatograms would lead to inaccurate results. We demonstrate a new method for computing a high quality alignment of full length MS chromatograms using variable penalty dynamic time warping. This method aligns signals using local linear shifts without excessive warping that can alter the shape (and area) of chromatogram peaks. The software is available as the R package VPdtw on the Comprehensive R Archive Network and we highlight how one can use this package here.
Journal of statistical software 01/2012; 47(8):1-17. · 4.91 Impact Factor
[show abstract][hide abstract] ABSTRACT: A key determinant of the efficiency of a surveillance system for exotic mites is whether an incursion might be detected sufficiently quickly to allow successful management actions to occur. To assess this possibility we have developed a spatial modeling system and synthesized knowledge of honeybee and mite behavior to explore the potential spread of exotic mites and the likelihood of their detection in sentinel hives. We find that increasing the number of hives and the efficiency of the detection method are the most effective means of improving the time to detection.
[show abstract][hide abstract] ABSTRACT: In this article we highlight a novel variation on dynamic time warping (DTW) for aligning chromatogram signals. We are interested in sets of signals that can be aligned well locally, but not globally, by shifting individual signals in time. This kind of alignment is often sufficient for aligning gas chromatography data. Regular DTW often "over-warps" signals and introduces artificial features into the aligned data. To overcome this we introduce a variable penalty into the DTW process. The penalty is added to the distance metric whenever a nondiagonal step is taken. We select our penalty based on a morphological dilation of the two signals. We showcase our method by aligning GC/MS datafiles from 712 blood plasma samples processed in 23 batches over the course of 6 months. The use of variable penalty DTW significantly reduces the number of nondiagonal moves. In the examples presented here, this reduction is by a factor of 30, with no cost to visual quality of the alignment.