Home  · Classes  · Annotated Classes  · Modules  · Members  · Namespaces  · Related Pages
SILACAnalyzer

Identifies peptide pairs in LC-MS data and determines their relative abundance.

pot. predecessor tools $ \longrightarrow $ SILACAnalyzer $ \longrightarrow $ pot. successor tools
FileConverter IDMapper
FileFilter

SILACAnalyzer is a tool for the fully automated analysis of quantitative proteomics data. It identifies pairs of isotopic envelopes with fixed m/z separation. It requires no prior sequence identification of the peptides. In what follows we first explain the algorithm and then discuss the tuning of its parameters.

Algorithm

The algorithm is divided into three parts: filtering, clustering and linear fitting, see Fig. (d), (e) and (f). In the following discussion let us consider a particular mass spectrum at retention time 1350 s, see Fig. (a). It contains a peptide of mass 1492 Da and its 6 Da heavier labelled counterpart. Both are doubly charged in this instance. Their isotopic envelopes therefore appear at 746 and 749 in the spectrum. The isotopic peaks within each envelope are separated by 0.5. The spectrum was recorded at finite intervals. In order to read accurate intensities at arbitrary m/z we spline-fit over the data, see Fig. (b).

We would like to search for such peptide pairs in our LC-MS data set. As a warm-up let us consider a standard intensity cut-off filter, see Fig. (c). Scanning through the entire m/z range (red dot) only data points with intensities above a certain threshold pass the filter. Unlike such a local filter, the filter used in our algorithm takes intensities at a range of m/z positions into account, see Fig. (d). A data point (red dot) passes if

Let us now filter not only a single spectrum but all spectra in our data set. Data points that pass the filter form clusters in the t-m/z plane, see Fig. (e). Each cluster corresponds to the mono-isotopic mass trace of the lightest peptide of a SILAC pattern. We now use hierarchical clustering methods to assign each data point to a specific cluster. The optimum number of clusters is determined by maximizing the silhouette width of the partitioning. Each data point in a cluster corresponds to three pairs of intensities (at [m/z, m/z+3], [m/z+0.5, m/z+3.5] and [m/z+1, m/z+4]). A plot of all intensity pairs in a cluster shows a clear linear correlation, see Fig. (f). Using linear regression we can determine the relative amounts of labelled and unlabelled peptides in the sample.

SILACAnalyzer_algorithm.png

The command line parameters of this tool are:

SILACAnalyzer -- Determination of peak ratios in LC-MS data
Version: 1.11.1 Nov 14 2013, 11:18:15, Revision: 11976

Usage:
  SILACAnalyzer <options>

This tool has algoritm parameters that are not shown here! Please check the ini file for a detailed descripti
on or use the --helphelp option.

Options (mandatory options marked with '*'):
  -in <file>*        Raw LC-MS data to be analyzed. (Profile data required. Will not work with centroided 
                     data!) (valid formats: 'mzML')
  -out <file>        Set of all identified peptide groups (i.e. peptide pairs or triplets or singlets or ..).
                     The m/z-RT positions correspond to the lightest peptide in each group. (valid formats:
                     'consensusXML')
                     
Common TOPP options:
  -ini <file>        Use the given TOPP INI file
  -threads <n>       Sets the number of threads allowed to be used by the TOPP tool (default: '1')
  -write_ini <file>  Writes the default configuration file
  --help             Shows options
  --helphelp         Shows all options (including advanced)

The following configuration subsections are valid:
 - algorithm   Parameters for the algorithm.
 - labels      Isotopic labels that can be specified in section 'sample'.
 - sample      Parameters describing the sample and its labels.

You can write an example INI file using the '-write_ini' option.
Documentation of subsection parameters can be found in the doxygen documentation or the INIFileEditor.
Have a look at the OpenMS documentation for more information.

INI file documentation of this tool:

Legend:
required parameter
advanced parameter
+SILACAnalyzerDetermination of peak ratios in LC-MS data
version1.11.1 Version of the tool that generated this parameters file.
++1Instance '1' section for 'SILACAnalyzer'
in Raw LC-MS data to be analyzed. (Profile data required. Will not work with centroided data!)input file*.mzML
out Set of all identified peptide groups (i.e. peptide pairs or triplets or singlets or ..). The m/z-RT positions correspond to the lightest peptide in each group.output file*.consensusXML
out_clusters Optional debug output containing data points passing all filters, hence belonging to a SILAC pattern. Points of the same colour correspond to the mono-isotopic peak of the lightest peptide in a pattern.output file*.consensusXML
out_features Optional output file containing the individual peptide features in 'out'.output file*.featureXML
out_mzq Optional output file of MzQuantML.output file*.mzq
out_filters Optional output file containing all points that passed the filters as txt. Suitable as input for 'in_filters' to perform clustering without preceding filtering process.output file*.consensusXML
in_filters Optional input file containing all points that passed the filters as txt. Use output from 'out_filters' to perform clustering only.input file*.consensusXML
out_debug Filename base for debug output.
log Name of log file (created only when specified)
debug0 Sets the debug level
threads1 Sets the number of threads allowed to be used by the TOPP tool
no_progressfalse Disables progress logging to command linetrue,false
testfalse Enables the test mode (needed for internal use only)true,false
+++algorithmParameters for the algorithm.
allow_missing_peaksfalse Low intensity peaks might be missing from the isotopic pattern of some of the peptides. Should such peptides be included in the analysis?true,false
rt_threshold30 Typical retention time [s] over which a characteristic peptide elutes. (This is not an upper bound. Peptides that elute for longer will be reported.)0:∞
rt_min0 Lower bound for the retention time [s].0:∞
intensity_cutoff1000 Lower bound for the intensity of isotopic peaks in a SILAC pattern.0:∞
intensity_correlation0.7 Lower bound for the Pearson correlation coefficient, which measures how well intensity profiles of different isotopic peaks correlate.0:1
model_deviation3 Upper bound on the factor by which the ratios of observed isotopic peaks are allowed to differ from the ratios of the theoretic averagine model, i.e. ( theoretic_ratio / model_deviation ) < observed_ratio < ( theoretic_ratio * model_deviation ).1:∞
+++labelsIsotopic labels that can be specified in section 'sample'.
Arg66.0201290268 Arg6 mass shift0:∞
Arg1010.0082686 Arg10 mass shift0:∞
Lys44.0251069836 Lys4 mass shift0:∞
Lys66.0201290268 Lys6 mass shift0:∞
Lys88.0141988132 Lys8 mass shift0:∞
dICPL44.025107 mass difference between isotope-coded protein labels ICPL 4 and ICPL 00:∞
dICPL66.020129 mass difference between isotope-coded protein labels ICPL 6 and ICPL 00:∞
dICPL1010.045236 mass difference between isotope-coded protein labels ICPL 10 and ICPL 00:∞
Methyl44.0202 Methyl4 mass shift0:∞
Methyl88.0202 Methyl8 mass shift0:∞
Methyl1212.0202 Methyl12 mass shift0:∞
Methyl1616.0202 Methyl16 mass shift0:∞
Methyl2424.0202 Methyl24 mass shift0:∞
Methyl3232.0202 Methyl32 mass shift0:∞
+++sampleParameters describing the sample and its labels.
labels[Lys8,Arg10] Labels used for labelling the sample. [...] specifies the labels for a single sample. For example, [Lys4,Arg6][Lys8,Arg10] describes a mixtures of three samples. One of them unlabelled, one labelled with Lys4 and Arg6 and a third one with Lys8 and Arg10. For permitted labels see 'advanced parameters', section 'labels'. If left empty the tool identifies singlets, i.e. acts as peptide feature finder (in this case, 'out_features' must be used for output instead of 'out').
charge2:4 Range of charge states in the sample, i.e. min charge : max charge.
missed_cleavages0 Maximum number of missed cleavages.0:∞
peaks_per_peptide3:5 Range of peaks per peptide in the sample, i.e. min peaks per peptide : max peaks per peptide. For example 3:6, if isotopic peptide patterns in the sample consist of either three, four, five or six isotopic peaks.

Parameter Tuning

SILACAnalyzer can detect SILAC patterns of any number of peptides, i.e. doublets (pairs), triplets, quadruplets et cetera.

input:

standard output:

optional output:

The results of an analysis can easily visualized within TOPPView. Simply load *.consensusXML and *.featureXML as layers over the original *.mzML.

Parameters in section algorithm:

Parameters in section sample:

Parameters in section labels: This section contains a list of all isotopic labels currently available for analysis of SILAC data with SILACAnalyzer.

References:
L. Nilse, M. Sturm, D. Trudgian, M. Salek, P. Sims, K. Carroll, S. Hubbard, SILACAnalyzer - a tool for differential quantitation of stable isotope derived data, in F. Masulli, L. Peterson, and R. Tagliaferri (Eds.): CIBB 2009, LNBI 6160, pp. 4555, 2010.


OpenMS / TOPP release 1.11.1 Documentation generated on Thu Nov 14 2013 11:19:24 using doxygen 1.8.5