Biology Reference
In-Depth Information
converter tools to generate mzXML files from mass spectrometer native
acquisition files. MSight has the advantage of a user-friendly interface,
which eases navigation through large volumes of data. Several visualiza-
tion tools allow one to discriminate peptide or protein from noise or to
perform differential analysis. Peak detection and peak alignment have
been integrated in its latest version, as has the semiautomatic analysis of
LC-MS datasets. The procedures for quantitative differential proteome
analysis are currently under development. MSight can also be considered
a resourceful tool for data quality control.
MZmine
18
and MapQuant
19
are open-source software packages for
LC/MS analysis written in Java and ANSI C, respectively. In MZmine,
several spectral filters are implemented to correct the raw data files, such
as smoothing for noise filtering of the mass spectra. Other methods are
also implemented, such as peak detection, peak alignment, and normaliza-
tion of multiple data files. Despite a user-friendly interface, the tool misses
statistical analysis procedures to quantify differences in a comparative study.
Other tools, such as XCMS,
20
SpecArray,
21
msInspect,
22
and
OpenMS,
23
automatically detect potential peptide features directly
from the raw data and extract the corresponding quantitative informa-
tion without the support of image analysis. Ion intensities are simply
integrated over time for measuring the total ion abundance for any
peptide ion within a LC-MS experiment. Some programs in the
SpecArray software suite
21
share functionalities with image analysis. In
a sequential mode, the Pep3D program generates 2-D gel-type images
from LC/MS data; the mzXML2dat program extracts high-quality
data by cleaning the spurious noise and creating centroid MS spectra;
the PepList program extracts a list of peptide features from LC/MS
data, such as the monoisotopic masses, the charges, and the retention
times of the MS spectra; the PepMatch program aligns peptide features
of multiple samples; and finally, the PepArray program generates an
array of peptide information. For each selected peptide present in each
sample, this program generates its normalized abundance value and its
retention time. These final arrays can be exported to a clustering tool
and then be further analyzed, i.e. to find quantitative differences in
LC/MS samples.
