Bioinformatics for LC-MS/MS-Based Proteomics - LC-MS/MS in Proteomics: Methods and Applications - page 70

Table 4.4
(Continued)

Complete pipelines
Proteios Software
Environment
( 102 )

http://www.proteios.org /

Trans-Proteomic
Pipeline ( 77 )

http://tools.proteomecenter.org/wiki/index.php?
title

Software:TPP
Elucidator System http://www.rosettabio.com/products/elucidator
Spotfire

=

http://spotfire.tibco.com/

5.1.Visualization
ofLC-MS/MSData

LC-MS/MS data are a fairly complex three-dimensional array of
structured data. The exact structure depends on the MS instru-
ment used to acquire the data and the analysis method. Visual-
ization of LC-MS/MS data with the precursors that lead to pep-
tide identifications can be very useful in assessing the quality of
the data. Data are typical plotted with m / z vs time and inten-
sity in the third dimension with interactive controls that allow
visual zooming and panning and data processing. Data-processing
options range from feature detection, background subtraction,
and charge state deconvolution to quantitation and multiple sam-
ple alignment and comparison or differential analysis. Precursors
that were analyzed by MS/MS may be marked in a different color
as are those that lead to a significant peptide identification.

5.2.Validatingand
ComparingSearch
Results

Not all the peptide and protein identification applications use a
true probabilistic scoring system; so an additional level of valida-
tion is often desired. LC-MS/MS data might be searched with
multiple search engines to gain further confidence in the pep-
tide assignments or to identify additional matches to those iden-
tified by only one of the search engines. The applications often
provide some level of false discovery rate (FDR) determination.
The results from multiple search engines can then be compared
and combined for the final interpretation and reporting. Statis-
tical analysis is also used to validate the database search engine's
spectra to peptide sequence and peptide to protein assignments
( 29 ) . Finally, further statistical analysis can be used to compare
and combine search results from different fractions or between
different search engine algorithms ( 30 ) . This allows for the anal-
ysis of large data sets containing multiple samples that have been
analyzed using the MudPIT ( 31 ) protocol or one-dimensional
gel electrophoresis in combination with LC-MS/MS (GeLC-
MS/MS). The complexity of the statistical analysis and combined
search results is such that the results are often visualized and
viewed in an interactive browser ( Table 4.4 ) .