Software:SpectraST

From SPCTools

SpectraST (short for "Spectra Search Tool" and rhymes with "contrast") is a spectral library building and searching tool designed primarily for shotgun proteomics applications. It is developed at the Institute for Systems Biology (ISB), in the research group of Professor Ruedi Aebersold. The main developer is Henry Lam.

The latest version of SpectraST is 5.0, released beta in November 2013, and officially with TPP 4.7 in March 2014. It is distributed by ISB under the LPGL license, as a component of the Trans Proteomic Pipeline (TPP) suite of software, distributed under the same license. The source code repository is at [1], and the official download site for the Windows installer is at [2].

Introduction to Shotgun Proteomics and Spectral Searching

The goal of proteomics is the systematic identification and quantification of all proteins in a biological system. In one of the most frequently practiced workflows, commonly known as shotgun proteomics, a protein sample of interest is first digested with a proteolytic enzyme (trypsin being the most common) to yield peptides that are amenable to LC-MS/MS analysis. The peptides in the resulting mixture are chromatographically resolved, ionized by techniques such as electrospray ionization (ESI) or matrix-assisted laser desorption ionization (MALDI) before being analyzed by a mass spectrometer. A fraction of the peptide ions are selectively isolated by the mass spectrometer and subjected to collision-induced dissociation (CID), in which the peptide ions are bombarded with noble gas atoms to induce fragmentation. (Other types of fragmentation techniques are also rapidly maturing.) The fragment ions are detected and reported by the mass spectrometer as tandem mass (MS/MS) spectra. Because peptide ions tend to fragment mostly along the peptide backbone in a somewhat predictable manner, the MS/MS spectra contain information that can be used to deduce the peptide sequence.

Traditionally, the inference of the peptide sequence from its characteristic tandem mass spectra is done by sequence (database) searching. In sequence searching, a target protein (or translated DNA) database is used as a reference to generate all possible putative peptide sequences by in silico digestion. The search engines then use various rules to predict the theoretical fragmentation pattern of each of these putative peptides, and compare the experimentally observed MS/MS spectra to these theoretical spectra one-by-one. Presumably, a positive identification is made if the experimental spectrum is sufficiently similar to one of the theoretical spectra. Several popular computational tools developed for this purpose have emerged over the years, each employing different algorithms and heuristics to achieve an acceptable balance of sensitivity and accuracy. Unfortunately, traditional sequence searching is a challenging, error-prone, and computationally expensive exercise. Despite the tremendous improvement in computer hardware and software over the past decade, this step often remains the bottleneck of any given proteomics experiment. The requirement of computational resources is also substantial, limiting the use of this powerful technique to only those research groups that can afford the costly computational infrastructure.

Spectral searching is an alternative approach that promises to address some of the shortcomings of sequence searching. In spectral searching, a spectral library is meticulously compiled from a large collection of previously observed and identified peptide MS/MS spectra. The unknown spectrum can then by identified by comparing it to all the candidates in the spectral library for the best match. This approach has been commonly employed for mass spectrometric analysis of small molecules with great success, but has only become possible for proteomics very recently. The main difficulty of generating enough high-quality experimental spectra for compilation into spectral libraries has been overcome by the recent explosion of proteomics data and the availability of public data repositories. Several attempts at creating and searching spectral libraries in the context of proteomics have been published within the past year, all demonstrating the tremendous improvement in search speed and the great potential of this method in complementing, if not replacing, sequence searching in many proteomics applications.

Advantages of Spectral Searching

1. Speed

Spectral searching benefits from a much reduced search space compared to sequence searching. In spectral searching, only peptide ions that are observed and identified in previous experiments will be included in spectral libraries and considered as candidates, whereas in sequence searching, all putative peptide sequences -- plus all permutations of post-translational modification sites, if specified -- in a protein database are considered. Most of these putative peptide ions considered in sequence searching are never observed in practice for a variety of reasons. With typical search parameters, the search space of spectral searching can be several orders of magnitude smaller. It is therefore not surprising that spectral searching can also be several orders of magnitude faster. SpectraST can achieve a top speed of 0.001 to 0.01 second per query spectrum (against a library of about 50,000 entries) on a modern personal computer. In contrast, SEQUEST, one of the most popular sequence search engine, needs about 5 to 20 seconds per query spectrum (against a human IPI database).

2. Preciseness

Spectral searching compares experimental spectra to experimental spectra; sequence searching compares experimental spectra to theoretical spectra. In general, the theoretical spectra considered in sequence searching are very simplistic (e.g., only including b- and y-type ions, at a fixed intensity), and do not resemble the experimental spectra that they are supposed to match. On the other hand, armed with previously observed experimental spectra compiled into spectral libraries, spectral searching can take full advantage of all spectral features, including actual peak intensities, neutral losses from fragments, and various uncommon or even unknown fragments, to determine the best match. The similarity scoring of spectral searching is therefore more precise, and will generally provide better discrimination between good and bad matches. This usually results in much superior statistics (e.g., sensitivity, false discovery rates) for the search results, compared to sequence searching.

Versions

What's new in SpectraST 5.0

• New, rank-based similarity scoring function (Old scoring function remains as an option)
• High mass accuracy MS2 (including HCD) support
• Spectral archive (unidentified spectral library) building
• Biological sample fingerprinting by spectral archives
• Open (blind) modification search
• Improved decoy generation, including alternative method by precursor swapping
• Semi-empirical spectrum generation for amino acid substitutions
• De-noising based on Bayesian classifier
• Retention time normalization using injected landmark peptides

What's new in SpectraST 4.0

• ETD support
• iProphet support
• Decoy spectrum generation
• MRM transition list generation
• User-defined modifications
• Semi-empirical spectrum generation from real spectrum of closely related identification
• Searching .mgf files
• Clickable (HTML) search output format
• Better book-keeping in library building
• Various bug fixes and performance enhancements

What's new in SpectraST 3.1

• Re-mapping peptide identifications of library entries to protein sequence database of choice
• Rudimentary centroiding for imported spectra in profile mode
• mzML support via TPP
• Various bug fixes and performance enhancements

What's new in SpectraST 3.0

• Creating libraries from sequence search results
• Library manipulation
  • Union/Intersect/Subtract operations
  • Consensus/Best-replicate library building
  • Filtering based on criteria
  • Quality filters
• Importing libraries from X!Hunter and BiblioSpec formats
• File list feature
• Logging
• Lib2HTML utility for visualizing library
• Monoisotopic mass support
• Various bug fixes and performance enhancements

What’s new in SpectraST 2.0

• Binary library format, enabling speed gain
• Library information and statistics in preambles of .sptxt and .pepidx files
• Searching of .dta files
• Detecting homologs in hit list
• Various bug fixes and performance enhancements

User's Guide

Installing SpectraST

SpectraST is an integral component of the Trans Proteomic Pipeline suite of software. Although it can be used alone without other TPP components, SpectraST users are strongly encouraged to download and install the entire TPP suite, which provides other useful functionalities such as raw data importation, automatic validation of search results, protein inference, and quantification and visualization.

Windows users: SpectraST is available as part of TPP for Windows. A one-click installer is available, in which Windows-native executables are compiled by MinGW.

UNIX/LINUX users: Visit the Sashimi project page on SourceForge.net, and download the code as a tarball directly. Compiling, installation and configuration information is available in the README file. Alternatively, follow the instructions for Ubuntu LINUX installation.

Running SpectraST

SpectraST has two modes, the Create mode and the Search mode. In the former, SpectraST creates a searchable spectral library from various formats to prepare for searching. In the latter, SpectraST takes in unknown spectra and searches each of them against the spectral library.

The simplest way of running SpectraST is from the command line of your UNIX/LINUX or Windows cmd shell. The general usage is:

spectrast <options> <list of files of appropriate formats>

Options must be separated by space, and all begin with a hyphen ('-'). Search mode options always have an 's' following the hyphen; Create mode options a 'c'. SpectraST will perform the appropriate action based on the options specified, and complain when there are problems interpreting the command statement. The usage statement, and a list of options can be viewed by issuing the command spectrast by itself.

Once TPP is installed, SpectraST can also be run from the Petunia web interface, with limited options.

SpectraST Search Mode

SpectraST can perform spectral searching from the following data formats:

• .mzML format
• .mzXML (all versions) format
• .mzData format
• .mgf (Mascot Generic) format
• .dta (SEQUEST) format, a simple peak list preceded by precursor information
• NIST (National Institute of Standards and Technology)’s .msp format

To search, the spectral library must be in SpectraST’s .splib format, which can be created in SpectraST Create Mode.

The results can be outputted to the following formats:

• .pepXML format
• .txt format, a fixed-width column text format
• .xls format, a tab-delimited column text format
• .html format, a HTML table with clickable links to spectrum viewer

The search mode is initiated with the option -s, or any of the search mode options. For instance, to search the MS/MS spectra in the file foo.mzXML against the spectral library bar.splib, using the parameters specified in the file spectrast.params, the command is simply:

spectrast -sFspectrast.params -sLbar.splib foo.mzXML

In the above, -sF and -sL are search mode options that the user can specify to customize the behavior of SpectraST. SpectraST will search all the MS/MS spectra in the file foo.mzXML against the spectral library bar.splib, using the parameters specified in the file spectrast.params. The result will be written to a file named foo.<ext> in the same directory where <ext> specifies the output format (.pep.xml, .txt, .xls, or .html).

For a full list of options, see SpectraST Options.

SpectraST Create Mode

Importing Existing Libraries

SpectraST can create a searchable spectral library from the following formats:

• NIST (National Institute of Standards and Technology)'s .msp format (Download here)
• X!Hunter's .hlf format [3]
• BiblioSpec’s .ms2 format [4]

If files of these extensions are supplied, SpectraST simply converts those spectral libraries into a form suitable for SpectraST searches (.splib formats). (Note however that there is no study on how well SpectraST works with X!Hunter and BiblioSpec libraries.) For instance, to import the NIST yeast consensus library, and call the resulting library bar.splib and put it in the directory /dir/, the command is:

spectrast -cN/dir/bar yeast_consensus.msp

When it is done, it produces 5 files in the directory /dir/. The file bar.splib is the library itself; it’s in a binary (machine-readable) format. The file bar.sptxt is a text (human-readable) version of bar.splib. This .sptxt file is of no use to SpectraST; it can be deleted after manual inspection. The files bar.spidx and bar.pepidx are indices on the precursor m/z value and peptide, respectively. Keep the indices and the .splib file in the same directory for SpectraST to function properly. Lastly, a file spectrast.log is also created to document the command executed. Some useful information about the library is printed at the beginning of the bar.sptxt and bar.pepidx.

For a full list of SpectraST options, see SpectraST Options.

Creating Libraries from Sequence Search Results

SpectraST can create a spectral library from a .pepXML file, which contains peptide identifications from a previous shotgun proteomics experiment. For this purpose, it is preferable that the .pepXML has been processed with PeptideProphet and/or iProphet, such that all the search hits have probabilities assigned. (iProphet probabilities are used over PeptideProphet ones if both are present.)

When importing from a .pepXML file, SpectraST scans through the .pepXML file for confident identifications, and attempts to extract the corresponding experimental spectra from .mzXML files. For instance, the command

spectrast -cNraw -cP0.9 dataset1.xml

will import all peptide identifications with probability at or above 0.9 from the file dataset1.xml, and put them in a library called raw.splib (with the accompanying raw.sptxt, raw.spidx and raw.pepidx files). For a full list of SpectraST options, see SpectraST Options.

Manipulating SpectraST Libraries

SpectraST can convert one or more .splib libraries to another, performing various operations. For instance, to create a consensus library from all the entries in bar.splib and foo.splib, the command is:

spectrast -cNconsensus -cJU -cAC bar.splib foo.splib

SpectraST will take the union (specified by the option -cJU) of all the entries in bar.splib and foo.splib, and wherever a certain peptide ion is present as multiple entries (replicates), it will coalesce the replicates into a single consensus spectrum (specified by -cAC).

Some additional examples:

spectrast -cNphospho -cf”Mods =~ Phospho” bar.splib

This will screen the library bar.splib for all entries with a phosphorylation modification, and put the phosphopeptides in the library phospho.splib.

spectrast -cNcommon -cJI dataset1.splib dataset2.splib

This will take the intersection of the two libraries dataset1.splib and dataset2.splib, and put all entries of peptide ions that are seen in both files in the library common.splib.

spectrast -cNquality -cAQ -cL2 bar.splib

This will apply SpectraST’s quality filters to the library bar.splib; only those entries that pass the first 2 quality filters will be included in the library quality.splib.

For a full list of SpectraST options, see SpectraST Options. For a typical recipe for creating consensus libraries from sequence search results, see Creating Consensus Libraries.

Creating Consensus Libraries

A recipe for creating consensus libraries from TPP-processed sequence search results is detailed here. Consider the following example:

The following commands should be issued in succession:

? -cNrawA -cnAlpha
A-SEQ.xml
A-MAS.xml
? -cNrawB -cnBeta
B1.xml
B2.xml
? -cNrawG -cnGamma
G.xml
? -cJU -cAC -cNconsABC
rawA.splib
rawB.splib
rawC.splib
? -cAQ -cNconsABC_Q
consABC.splib

1. Importing the raw spectra into SpectraST
spectrast -cNrawA -cnAlpha A-SEQ.xml A.MAS.xml
spectrast -cNrawB -cnBeta B1.xml B2.xml
spectrast -cNrawG -cnGamma G.xml

These commands will create the raw libraries rawA.splib, rawB.splib and rawC.splib. Identifications from multiple .pepXML files of the same dataset are imported with the same dataset identifier. The same query with identifications from multiple search engines will be combined intelligently. The probability threshold above which identifications are imported can be specified with the option -cP<prob>, which defaults to 0.9. This will not coalesce replicates of the same peptide ion identification into a consensus spectrum yet. Remember that the .mzXML files must be in the same directories as their corresponding .pepXML files.

2. Creating a consensus spectral library
spectrast -cJU -cAC -cNconsABC raw*.splib

This will combine the three raw libraries, then replace multiple replicates of the same peptide ion identification with a consensus spectrum. Many options are available to fine-tune the algorithm; however, the default parameters are usually adequate.

3. Performing quality control of the consensus spectral library
spectrast -cAQ -cNconsABC_Q consABC.splib

This will run the consensus spectra through SpectraST's quality filters. With the default settings, spectra failing either or both of the first 2 filters will be removed, and spectra failing any of the other filters will be marked. Different quality levels can be set with the options -cL and -cl. It is recommended that a consensus spectral library is subject to some quality control before using it in spectral searching; the optimal quality level reflects the user's desired compromise between library comprehensiveness and library quality. This is to minimize mis-identified and low-quality spectra in the library. These questionable spectra can propagate errors from sequence searching, reduce the discriminating power of the spectral search engine, and induce false positive and false negative hits.

For details on the consensus and quality filter algorithms, please refer to Lam et al. (2008) Nature Methods 5, 873-875.

4. Appending artificial decoy spectra
spectrast -cAD -cc -cy1 -cNcons_ABC_Q_DECOY

This will generate an equal-size decoy spectral library and append it to the real library consABD_Q.splib. The presence of decoys enables the estimation of false discovery rate (FDR) by the well-established decoy counting method, and improves the accuracy of PeptideProphet in validating spectral search results.

The algorithm of generating artificial decoy spectra is described in Lam et al. (2010) Journal of Proteome Research 9, 605-610.

Miscellaneous Features

SpectraST Parameter Files

SpectraST allows the use of parameter files to simplify the process of spectral library building and searching. Namely, desired options can be specified in a text file, and supplied to SpectraST every time the same action is performed, saving the user from having to specify lengthy list of command-line options. To invoke the parameter files, specify the options -sF<parameter file> and -cF<parameter file> for Search Mode and Create Mode, respectively. Exemplary parameters file are provided below (these are essentially the defaults):

Search Mode: spectrast.params

Create Mode: spectrast_create.params

High Mass Accuracy MS2 Support

As of version 5.0, SpectraST supports the handling of high mass accuracy MS2 spectra (including higher-energy collisional dissociation, HCD, spectra). The fragmentation methods CID-QTOF and HCD are created to tag such spectra, and that information is automatically extracted from the data (.mzML/.mzXML) files (if specified therein) for library building. The user can also explicitly specify the fragmentation method, using the -cI option.

When building libraries, SpectraST annotates and aligns CID-QTOF/HCD spectra differently, using a narrower tolerance and considering immonium ions and internal fragments. However, when searching, the user must still specifies the "bin size" (equivalent to the product ion tolerance) as the mass accuracy can vary from instrument to instrument.

Spectral Archive (Unidentified Spectral Library) Building

As of version 5.0, SpectraST can also build and search spectral libraries without identifications. Such libraries are also referred to as spectral archives. The spectral archive building prodecure is as follows:

spectrast -cNraw_unid foo.mzXML

This imports all MS2 spectra in foo.mzXML into the library raw_unid.splib, with some filtering and merging. Each spectrum will be given a unique identifier starting with an underscore '_' in place of the peptide identification.

spectrast -cNclustered_unid -cAS raw_unid.splib

This performs spectral clustering, such that replicate spectra of similar precursor m/z and high spectral similarity are detected and merged into consensus spectra.

Advanced options -c_UCR, -c_UCD, -c_UX1, -c_UNP and -c_USX control some tunable parameters of this procedure.

Spectral archives can be searched by SpectraST in the same way as identified spectral libraries, such as for biological sample fingerprinting (see below). Please note that results obtained by searching spectral archives may not be recognized by downstream TPP tools.

Biological Sample Fingerprinting by Spectral Archives

Spectral archives can be used for biological sample fingerprinting. As of version 5.0, upon searching such libraries, SpectraST can output a text file reporting "dataset similarities" calculated from counting spectral matches of library spectra from different sources (with -s_FIN option). The details of this algorithm and the instructions can be found in Onders et al. (2014) Nature Protocols 9, 842-850.

Open (Blind) Modification Search

As of version 5.0, SpectraST can perform open (blind) modification search using the algorithm published in Ma et al. (2014) Journal of Proteome Research 13, 2262-71.

De-noising by Bayesian Classifier

As of version 5.0, SpectraST implements the algorithm published in Shao et al. (2013) Journal of Proteome Research 12, 3223-32 for de-noising singleton library spectra.

Retention Time Normalization using Injected Landmark Peptides

As of version 5.0, SpectraST can make use of injected standard peptides to calculate a normalized retention time index (iRT) to be included in the library entry, which removes the variability due to LC settings and columns. This enables retention time information to be used in SWATH/SRM assays, among other uses. It implements two different ways of calculating iRT, linear regression and linear interpolation.

ETD Support

As of version 4.0, SpectraST supports the import and searching of MS2 spectra by electron-transfer dissociation (ETD). A tag encoding the fragmentation method is added to each library entry to differentiate between CID (collision-induced dissociation) and ETD spectra, and that information is automatically extracted from the data (.mzML/.mzXML) files (if specified therein) for library building. The user can also explicitly specify the fragmentation method, using the -cI option.

SpectraST annotates ETD spectra differently than CID spectra, and the spectral matching algorithm is slightly modified to deal with the charged-reduced precursor peaks common in ETD spectra.

Generation of Transition Lists for Selected/Multiple Reaction Monitoring (S/MRM)

Selected reaction monitoring (SRM, also known as Multiple Reaction Monitoring, MRM) is an acquisition mode available on some mass spectrometers (mostly triple quadrupole instruments) which has gained increasing popularity as a targeted quantification technique. It requires as input a list of “transitions” to be monitored over the course of the experiment. Each transition consists of two numbers, Q1 (the precursor m/z) and Q3 (the fragment ion m/z) and must be selected beforehand based on knowledge of the peptide to be quantified. One of the most effective strategies for selecting appropriate transitions is to rely on previously acquired MS2 spectra of the target peptides stored in spectral libraries.

As of version 4.0, SpectraST implements an algorithm to select the N (a user-specified number) most suitable transitions for each library spectrum, and print the list of transitions in a table format. For example, the command:

spectrast -cNfoo_MRM -cM -cQ5 foo.splib

will create a “reduced” spectral library foo_MRM.splib, in which only each spectrum only retains the 5 peaks most suited as MRM transitions. In addition, a text file foo_MRM.mrm containing the transitions in a table format will be printed.

A fully functional software tool for MRM experiment design, MaRiMba (Sherwood et al. (2009) Journal of Proteome Research 8, 4396-4405), which essentially wraps this transition selection algorithm of SpectraST as well as implements some surrounding functionalities, is freely available as part of the TPP and accessible via the Petunia web interface.

User-defined Modifications

As of version 4.0, users can specify allowable modifications in a text file. (Prior to 4.0, SpectraST internally maintains a list of common modifications and will reject identifications with unrecognized modifications.) This text file should contain space- or comma-delimited strings of the following form:

<token>|<monoisotopic mass change from unmodified amino acid>|<name of modification>

where <token> must be one of the amino acids in one-letter code (capitalized), n (the N terminus) or c (the C terminus), optionally followed by [<tag>], a user-defined short tag for that modification, and <name of modification> is a user-defined formal name of that modification which will be written to the library created.

An example of this file can be found in spectrast.usermods.

To activate the modifications specified in this file, add the option -M to the command line whether identifications containing these modifications are to be processed. By default, SpectraST expects the file to be named spectrast.usermods and reside in the current working directory. You can also specify otherwise by appending the file name (with path if necessary) after the -M.

Since a spectral library is meant to be a long-lasting and shared resource, special care should be taken in specifying new modifications. Accurate monoisotopic masses (preferably to at least 4 digits) should be used, and the name of the modification should follow HUPO-PSI convention as much as possible. Consult Unimod to see if your modification is already defined in HUPO-PSI standards.

Semi-empirical Spectrum Generation

As of version 4.0, SpectraST can generate semi-empirical spectra from real spectra of closely-related identifications, simply by shifting peaks on the m/z axis wherever appropriate. This is useful when spectra of one modification state are used to built the library, but one wishes to match spectra of the same sequence but another modification state in spectral searching.

To do so, the user needs to turn on the build action of semi-empirical spectrum generation by the option -cAM, and specify what modifications are desired by the -cx<str> option. The <str> in the latter is a string of allowable modification tokens (no space in between). A modification token starts with a one-letter amino acid (A through Z, plus n or c for the termini), followed by [<tag>] if it is not the unmodified form.

For example, the command

spectrast -cNfoo_heavy -cAM -cx’K[134]R[162]’ foo.splib

will create a library foo_heavy.splib containing the same peptide ions as foo.splib, but with all lysines and arginines being heavy (both +6 Da). Note that since K and R are not included in the string following -cx, unmodified K or R is not allowed to be used. This is commonly referred to as a static modification.

The command

spectrast -cNfoo_metox -cAM -cx’MM[147]’ foo.splib

will create a library foo_metox.splib containing the same peptide ions as foo.splib, but with all possible permutations of normal and oxidized methionine. This is commonly referred to as a variable modification. Note that the string ’MM[147]’ means that both M (normal methionine) and M[147] (oxidized methionine) are allowed where an M is present in a sequence.

The command

spectrast -cNfoo_binary -cAM -cx’{K}{K[134]}’ foo.splib

specifies a “binary” modification: lysines on the same peptide must be either all light or all heavy. The curly bracelet ({ }) specifies sets of allowable modification tokens; for the same peptide only tokens from a single set can be used.

Note that while the modification tokens, such as M[147], contain only integer values (of the modified amino acids) as a tag, in calculations SpectraST will use the corresponding accurate mass stored for that particular modification type indicated by the token. Hence, for modifications currently not recognized by SpectraST, the user must define them (along with the accurate mass) in a text file using the -M option.

SpectraST File List Feature

SpectraST allows the user to list the files to be processed in a text file with extension .list. This can be useful when the number of files to be processed is very large, possibly overwhelming the UNIX command line. It is also an easy way to queue up multiple SpectraST tasks and to keep track of them. For example, if the file job.list contains the lines:

# This is a comment line ignored by SpectraST.
? -sLfoo.splib   # '?' signals the start of a new job; options for this job follow the '?'
1.mzXML
2.mzXML

? -sLbar.splib
3.mzXML
4.mzXML

Then running the command:

spectrast -sFspectrast.params job.list

is equivalent to running

spectrast -sFspectrast.params -sLfoo.splib 1.mzXML 2.mzXML

followed by

spectrast -sFspectrast.params -sLbar.splib 3.mzXML 4.mzXML

SpectraST Options

Commonly used options are shown in bold. The rest are advanced options that should rarely need to be used.

Other SpectraST Utilities

Plotspectrast

Plotspectrast is a spectrum viewer designed for SpectraST. It comes as two programs: a CGI that can be launched from a web page (e.g., from PepXMLViewer), and a stand-alone application. They are included in the TPP and no additional installation is necessary.

The most common use of Plotspectrast is for visualization of spectral matches from PepXMLViewer. When displaying SpectraST results, PepXMLViewer provides a link to invoke plotspectrast.cgi for each spectrum query. The query spectrum will be plotted as a "mirror image" of the best-matched library spectrum, enabling the user to quickly assess the quality of the match. Below the plot there is an ion table, and tables listing information about the library spectrum. The legend of the plots and ion table is as follows:

Various controls are available to the left of the plot to customize how the spectra are displayed:

The stand-alone plotspectrast application produces a static .png image in the same directory as the query spectrum file. It has the following usage:

plotspectrast <.splib file> <library file offset> <.mzXML file> <query scan number>

Plots the library spectrum at <library file offset> and the query spectrum of <query scan number> in the .mzXML file. The desired value of <library file offset> can be extracted from the .spidx, .pepidx or .sptxt file (BinaryFileOffset in the Comment field).

plotspectrast <.splib file> <library file offset> <.dta file>

Similar to above, except the query spectrum is in a .dta file.

plotspectrast <.splib file> <library file offset> <.none file>

Plots the library spectrum by itself. It will not actually look for the .none file, but the resulting .jpg file will be named with the same prefix as the .none file and place in the same directory.

plotspectrast <.msp file of library spectrum> <.msp, .dta, or .none file>

Similar to above, except the library spectrum is given in a .msp file.

plotspectrast <.splib file 1> <library file offset 1> <.splib file 2> <library file offset 2>

Plots two library spectra head to tail.

Lib2HTML

Lib2HTML is an application that converts a SpectraST library into an HTML file for viewing. It is included in the TPP and no additional installation is necessary. In the resulting HTML file, replicates of the same peptide ion will be listed on one row, and links are provided to each replicate to view the spectrum using Plotspectrast. The usage is:

Lib2HTML <options> <full path from webserver root to .splib file>

Options include:

• -V : Verbose. Displaying more information for each entry.
• -N<num> : Specify the maximum number of replicates displayed for each unique peptide ion. Default is 10.
• -P<path> : Specify the full path from the webserver root to the plotspectrast.cgi binary.

Developer's Guide

The SpectraST source code contains detailed documentation.

sptxt file format:

The sptxt file format is very closely realted to the msp format, whose documentation can be found here.

Annotation syntax:

SpectraST's syntax to annotate a fragment follows the scheme proposed by Roepstorff and Fohlman.

An annotation tag starts with the assigned ion type (a,b,c,x,y or z) and is followed by the number of amino acid residues present in the fragment. This number is possibly followed by a signed integer value, indicating a modification. Please note that besides post-translational modifications also loss of water (-18) and loss of ammonia (-17), e.g., are taken into account. The caret symbol '^' followed by an integer value depicts the charge state of the fragment. Its absence indicates a singly charged fragment ion. An additional 'i' at the end of the annotation tag implies that the mass value does not correspond to the expected mass value of the monoisotopic peak, but can be assigned to a different isotopic peak of the fragment. Finally, the annotation pattern contains the average mass deviation (in Da) from the theoretically expected mass. A slash '/' preceds this number.

The list of possible annotations is ordered by ascending charge states, where ties are broken by ascending mass deviations.

Annotation tags can be enclosed by square brackets, indicating that several peaks could be assigned the same particular ion. Usually, SpectraST would resolve such a situation by annotating only one of the ions and leaving the other ones blank. If data is not (sufficiently) centroided, this strategy might lead to a buch of unresolved peaks, which might in turn cause quality filters to fail. To circumvent this problem, if there are additional intense peaks that look to be the same ion, a bracketed annotation will be given to them.

Besides annotations following the Roepstorff/Fohlman notation SpectraST also assigns immonium ions. The corresponding tag consists of 3 capital letters, always starting with an 'I' (for immonium), followed by the amino acid and an additional letter to designate different residue-specific ions from that amino acid.

More tips to developers who want to modify SpectraST will be available shortly.

Where to Get Help

The SPC Tools Discussion Group: spctools-discuss.googlegroups.com

The SPC Tools Announcement Group: spctools-announce.googlegroups.com

Public spectral libraries are available for download at PeptideAtlas

External Links

• Institute for Systems Biology
• Sashimi Project on SourceForge.net
• Seattle Proteome Center Software
• spctools-discuss.googlegroups.com
• spctools-announce.googlegroups.com
• PeptideAtlas's Spectral Library Page
• GPM's X!Hunter Project
• BiblioSpec Project at University of Washington

Reference

• Keller, Andrew, et al. (2005) "A uniform proteomics MS/MS analysis platform utilizing open XML file formats". Molecular Systems Biology 1, 17. Full text

• Lam, Henry, et al. (2007). "Development and validation of a spectral library searching method for peptide identification from MS/MS". Proteomics 7 (5), 655-667. Abstract

• Craig, Robertson, et al. (2006). "Using annotated peptide mass spectrum libraries for protein identification". Journal of Proteome Research 5 (8), 1843-1849. Abstract

• Frewen, Barbara, et al. (2006). "Analysis of peptide MS/MS spectra from large-scale proteomics experiments using spectrum libraries". Analytical Chemistry 78 (16), 5678-5684. Abstract

• Lam, Henry, et al. (2008). "Building consensus spectral libraries for peptide identifications in proteomics". Nature Methods 5, 873-875. FullText

• Picotti, Paola, et al. (2008). "A database of validated assays for the targeted mass spectrometric analysis of the S. cerevisiae proteome". Nature Methods 5, 913-914. FullText

• Sherwood, Carly, et al. (2009). "MaRiMba: A software application for spectral library-based MRM transition list assembly ". Journal of Proteome Research 8, 4396-4405. Abstract

• Lam, Henry, et al. (2010). " Artificial decoy spectral libraries for false discovery rate estimation in spectral library searching in proteomics". Journal of Proteome Research 9, 605-610. Abstract