Visual Representation of Mass Spectrometric Data
To visualize and analyze mass spectrometric data the software Spectromania was developed. All mass spectra are combined for each individual sample to a two-dimensional display of peptides based on their molecular masses and elution characteristics. The intensity of each mass-spectrometric signal is translated into color intensity.
Each mass spectrometric file is automatically converted into a gel-like view: The intensity is depicted as a shade of color. The view changes from a front view to a top view. This steps improves the perception of multi-dimensional data.
The figure demonstrates the conversion of a mass spectra (top) to a gel-like view (bottom). The intensity is depicted as a shade of color and can be adjusted in various ways to optimize the view for the specific experimental serie.
The figure shows the basic concept of multi-dimensional displays of mass spectrometric data. Each mass spectra is aligned to a display depicting MS signals as dots. Mass spectra derived from one fractionated sample are grouped. The intensity and area corresponds to the measured signal intensity. The colored circles indicate signals as examples which were transformed from a front view to a top view.
Each display consists of 1-20 Mill. datapoints. The number depends on the actual binning of the data.
Each display consists of 1-20 Mill. datapoints. The number depends on the actual binning of the data.
The figure shows an example of complex data structures.
The sample was separated based on hydrophobicity (the later a peak appears the more hydrophobic the substance is) and each fraction was measured by mass spectrometry. The spectrum at the bottom refers to the lane marked with red dashed lines.
The sample was separated based on hydrophobicity (the later a peak appears the more hydrophobic the substance is) and each fraction was measured by mass spectrometry. The spectrum at the bottom refers to the lane marked with red dashed lines.
The display shows:
1. Hydroxylations cause chromatographic shifts towards hydrophilicity
2. Thymosin-ß4 (Tyb4) shows different modifications (AC=acetylation, ox=oxidation)
3. If an oxidation occurs after chromatography the product can be found within the same fraction (AC-Tyb-4-ox)
4. If an oxidation occurs prior to chromatography the resulting product exhibit a chromatographic shift (Tyb-4-sulfoxide)
1. Hydroxylations cause chromatographic shifts towards hydrophilicity
2. Thymosin-ß4 (Tyb4) shows different modifications (AC=acetylation, ox=oxidation)
3. If an oxidation occurs after chromatography the product can be found within the same fraction (AC-Tyb-4-ox)
4. If an oxidation occurs prior to chromatography the resulting product exhibit a chromatographic shift (Tyb-4-sulfoxide)
Resources
Literature:
Datamining methodology for LC-MALDI-MS based peptide profiling
[ Comb Chem High Throughput Screen. 2005 Dec;8(8):717-23]
MSight: an image analysis software for liquid chromatography-mass spectrometry
[Proteomics. 2005 Jun;5(9):2381-4]
Literature:
Datamining methodology for LC-MALDI-MS based peptide profiling
[ Comb Chem High Throughput Screen. 2005 Dec;8(8):717-23]
MSight: an image analysis software for liquid chromatography-mass spectrometry
[Proteomics. 2005 Jun;5(9):2381-4]
The software allows to group or align mass spectra. These spectra are normally derived from samples separated by chromatographic methods. It is possible to visualize either mass spectra derived from the very same sample or mass spectra derived from different samples but the same fraction(s). This offers the opportunity to compare data based on a fraction model or based on the entire sample.
Basic Principle
Mining or analysis of data obtained by mass spectrometry to unravel relevant information can be done by a plethora of software tools. These tools mainly rely on extracted signal intensities from pre-defined peaks and normally do not use the entire information present in a mass spectrum. Furthermore relations between peaks in different spectra are often hard to recognize due to the diverse nature of these relations (e.g. mass shifts or adducts). However the result of data mining procedures has to be interpreted at the end with mass spectrometric expertise. One possibility to overcome these issues is the visualization of mass spectrometric data by a convenient but powerful approach.
Data analysis of mass spectrometric data can be a challenging task. Due to the overwhelming amount of data generated by modern mass spectrometers it is sometimes demanding to extract the relevant information.
Therefore Spectromania was developed. It started as an in-house project and was internally extensively used. Since we got lots of request for our software, we decided to make it publicly available.
Therefore Spectromania was developed. It started as an in-house project and was internally extensively used. Since we got lots of request for our software, we decided to make it publicly available.
Why Spectromania ?
Spectromania
... helps to assess mass spectrometric data by a combination of visualization and data analysis tools.
... can handle large amounts of data by storing datasets in an integrated database. This allows a quick access to relevant datasets.
... is designed to used not only by mass spectrometric specialists, but also by every scientist.
... helps to assess mass spectrometric data by a combination of visualization and data analysis tools.
... can handle large amounts of data by storing datasets in an integrated database. This allows a quick access to relevant datasets.
... is designed to used not only by mass spectrometric specialists, but also by every scientist.
- Spectromania is made by scientists for scientists -
