Visualisation tool for sets comparison

The visualisation tool to show the amount of common objects between the peak lists of interest (for all occurring possibilities) was initially developed to investigate the unexpected observation of a very high number of peaks in the blank mass spectrum - an extract blank prepared using identical methods of sample preparation but with no biological material added to the solvents. This number was comparable to the number of peaks detected for the biological samples, therefore a visualisation tool was developed to reveal whether these peaks were common to all the biological samples in this experiment or whether there were specific to blank spectrum, possibly offering some additional insight into this phenomenon.

4.3.1 Realisation

As an alternative to intersecting geometrical shapes as circles or ellipses that are used in Venn Diagrams, it was assumed that it is possible to represent the relationships between the sets via a series of horizontal bars. These bars are colour-coded to denote the amount of objects common between the sets for all of the logical possibilities (Figure 4.4). One of the sets can be marked as a reference one, with its colour-coded bars to be displayed at the very top of the diagram and a bar indicative of the amount of the specific only to this set elements (not present in the remaining

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sets) drawn to the very left of the graph (here used for the extract blank) The remaining sets are being added below the reference set, with their corresponding colour-coded bars arranged in a decreasing order, e.g. the number of elements common among the four sets (reference set and the three other sets) followed by the number of elements common among the three other sets, followed by number of elements common among only two sets and finally the number of elements specific to each of the three other sets (towards the right hand side of the diagram). The size of each coloured bar represents the number of elements falling into each specific category (logical possibility, e.g. common among the three other sets) and can be estimated based on the x- axis. The exact numbers of these elements are saved in the output text file.

Representing each set as a horizontal bar, divided into colour-coded regions, enables effortless comparisons of any number of sets since adding a set requires simply appending another horizontal bar below the already present ones, therefore eliminating the necessity to introduce non-congruent shapes. Also, the visual understanding and interpretation of the results is straightforward, even when considering higher number (n>4) of sets.

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Figure 4.4 Graphical representation of all the interactions between the reference set and three other sets; CCLp

datasets used here for illustration purposes; reference set: blank; set 1: control samples; set 2: samples exposed to indomethacin; set 3: samples exposed to medroxyprogesterone acetate

4.3.2 Applicability to signal processing in a metabolomics experiment

The comparable to biological samples number of peaks detected for the extract blank was initially observed while performing one of the first environmental studies of toxicity testing in

Daphnia magna employing the DI FT-ICR mass spectrometry metabolomics and the novel SIM-

stitching algorithm for the metabolites detection at the Environmental Metabolomics Research Laboratory, University of Birmingham (Taylor, Weber et al. 2009). The extract blank contained several thousand of peaks, similar to the number of peaks in the biological samples of the analysed Daphnia magna dataset. This observation was unexpected, since extract blank is prepared following the same protocol as used for the preparation of the biological samples, but with no biological material added (see Chapters 1 and 2). Quite opposite, one would anticipate to detect only a small set of peaks reflecting the presence of methanol, water and formic acid or ammonium acetate for positive and negative ion mode of analysis respectively.

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With the aid of the developed visualisation tool, it was shown that the majority of peaks occurring in the extract blank spectrum become suppressed as soon as biological material (metabolites) are added. It was speculated that the peaks measured for the biological samples are the ones of higher concentrations and therefore must have successfully competed for charge during the electrospray ionisation process. The peaks present in extract blank, on the other hand, are likely to include contaminants from the air and/or substances leaking from the plastic sample preparation tubes (plasticisers). Thes results highlight the analytical sensitivity of DI FT-ICR mass spectrometry. This theory is further supported when comparing the extract blank mass spectra obtained throughout various metabolomics studies, e.g. analyzing the cancer cell line,

Daphnia magna and human liver datasets (as described Chapter 2)(Figure 4.5). Among these

three quite different datasets, there were approximately 500 peaks common across the extract blank mass spectra, both for the positive and the negative ion mode of analyses. This phenomenon is a clear demonstration of the finite dynamic range of the DI FT-ICR mass spectrometry detector, which is all now being accounted for during the signal processing stage. In addition to the three stage noise filtering strategy (Chapter 1) peaks present in the extract blank spectrum are being removed from the biological samples spectra based on a user’s pre-defined settings, typically these peaks are being removed if they are more intense in the extract blank spectrum than in the biological spectra. The first successful application of this tool was in the same environmental study for which the observation of the high number of peaks for the extract blank was made with the results published in Metabolomics: Taylor, N., R. Weber, et al. (2009). "A new approach to toxicity testing in Daphnia magna: application of high throughput FT-ICR mass spectrometry metabolomics." Metabolomics 5(1): 44-58.

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Figure 4.5 The amount of peaks for all the possibilities among the three extract blank spectra obtained for CCLn,

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CHAPTER 5