TraML – a standard format for exchange of
selected reaction monitoring transition lists
Eric W. Deutsch1,*, Matthew Chambers2, Steffen Neumann3, Fredrik Levander4, Pierre-
Alain Binz5,6, Jim Shofstahl7, David S. Campbell1, Luis Mendoza1, David Ovelleiro8,
Kenny Helsens9,10, Lennart Martens9,10, Ruedi Aebersold11,12,13, Robert L. Moritz1, and
1 Institute for Systems Biology, Seattle, USA
2 Vanderbilt University, Nashville, USA
3 Department of Stress- and Developmental Biology, Leibniz Institute of Plant
Biochemistry, Halle, Germany
4 Department of Immunotechnology and CREATE Health, Lund University, Lund,
5 Geneva Bioinformatics (GeneBio) SA, Geneva, Switzerland
6 Swiss Institute of Bioinformatics, Geneva, Switzerland
7 Thermo Fisher Scientific, San Jose, CA, USA
8 EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
9 Department of Medical Protein Research, VIB, Ghent, Belgium
10 Department of Biochemistry, Ghent University, Ghent, Belgium
11 Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich,
12 Faculty of Sciences, University of Zurich, Zurich, Switzerland
13 Center for Systems Physiology and Metabolic Diseases, Zurich Switzerland
* Corresponding author: Eric W. Deutsch, Institute for Systems Biology, 401 Terry Ave
North, Seattle WA 98109, USA. Tel: 206-732-1397
Targeted proteomics via selected reaction monitoring (SRM) is a powerful mass
spectrometric technique affording higher dynamic range, increased specificity and lower
limits of detection than other shotgun mass spectrometry methods when applied to
proteome analyses. However, it involves selective measurement of predetermined
analytes, which requires more preparation in the form of selecting appropriate signatures
for the proteins and peptides that are to be targeted. There is a growing number of
software programs and resources for selecting optimal transitions and the instrument
MCP Papers in Press. Published on December 12, 2011 as Manuscript R111.015040
Copyright 2011 by The American Society for Biochemistry and Molecular Biology, Inc.
settings used for the detection and quantification of the targeted peptides, but the
exchange of this information is hindered by a lack of a standard format. We have
developed a new standardized format, called TraML, for encoding transition lists and
associated metadata. In addition to introducing the TraML format, we demonstrate
several implementations across the community, and provide semantic validators,
extensive documentation, and multiple example instances to demonstrate correctly
written documents. Widespread use of TraML will facilitate the exchange of transitions,
reduce time spent handling incompatible list formats, increase the reusability of
previously optimized transitions, and thus accelerate the widespread adoption of targeted
proteomics via SRM.
Targeted proteomics using selected reaction monitoring (SRM) (also referred to as
multiple reaction monitoring (MRM)) is a powerful technique that is widely used to
quantify small molecules in complex matrices. More recently introduced in proteomics, it
supports the identification and quantification of predetermined sets of peptides in
complex samples, with a low limit of detection, wide dynamic range, high reproducibility
and minimal redundancy (1-2). For this technique, a specific mass spectrometric assay
has to be developed once for each protein. Such assays are typically characterized by the
identity of the analyte (i.e. peptide amino acid sequence), the parent ion m/z value, the
approximate expected retention time of the targeted peptides, and the m/z and relative
signal intensity of product ions that are specifically associated with each precursor ion.
These measures, if detected, uniquely identify the targeted peptide in a complex sample.
The assays are generally optimized with respect to their fragmentation pattern with the
background matrix of the sample origin (i.e., plasma or cellular lysate). SRM assays can
also be conducted using either native protein digests to detect targeted proteotypic
peptides or can be incorporated in affinity capture routines such as N-glycocapture(3) or
immunoaffinity isolation(4), to decrease complex digest solutions and increase both
specificity and sensitivity to levels well within the pg/mL range(5). Since these assays
need to be generated only once per peptide and are increasingly publicly accessible in
publications and databases, a generally accepted and transparent format for
communicating SRM assays is a significant advance for this powerful targeted
At present, a wide array of software tools are available to predict, select, validate and
optimize transitions, such as TIQAM(6), Skyline(7), ATAQS(8), as well as commercial
offerings such as MRMPilot, Pinpoint, MassHunter, and VerifyE, from AB SCIEX,
Thermo Scientific, Agilent, and Waters, respectively. These tools use a variety of
different, mostly tabular formats. Furthermore, emerging resources and tools for the
generation and databasing of transitions such as PeptideAtlas(9-10), SRMAtlas(11-12),
MRMaid(13), MRMaid-DB(14), GPMDB(15), PASSEL(16), and QuAD
(http://proteome.moffitt.org/QUAD) also support different formats.
The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI; (17))
has been instrumental in developing and supporting several standards for mass
spectrometry data, including mzML(18-19) for mass spectrometer output files and
mzIdentML(20) for the results of proteomics data processing. Each of the PSI formats is
developed with similar concepts, such as controlled vocabularies and semantic validators.
They follow a rigorous approval process that ensures that PSI formats are well tested and
Towards unifying the fragmented state of SRM transition list formats, and facilitating
communication between resources, tools and instruments, the HUPO PSI Mass
Spectrometry Standards Working Group has developed a new standardized format,
TraML, that can be used to archive, share, and manage transition lists. In the following
sections we describe the basic structure of the format, several use cases, and existing
Figure 1. TraML is a common, standard exchange format between published
transition lists, transitions available in public or private databases, SRM design and
analysis software, and instrument control software, as well as a bridge to legacy
transition lists primarily stored in tab-delimited files or Excel worksheets
As summarized in Figure 1, TraML is intended as a standardized format that can serve as
an interchange between several components: published journal articles that include
transition lists as part of their methods; transition databases such as MRMaid, MRMaid-
DB, SRMAtlas, PASSEL, and QuAD that provide recommended transitions based on
user input; the many existing transitions lists that are already in common use; SRM
experiment design and analysis software such as ATAQS, TIQAM, Skyline, and others;
and the instruments themselves via their control software. If all or most of these tools can
exchange annotated transition lists in a common format, the hassle of transforming one
format to another is severely reduced if not altogether eliminated.
TraML builds on the same design concepts that were used for mzML and mzIdentML.
Like these formats previously developed for different data types, TraML is based on
Extensible Markup Language (XML) and can be parsed and validated for structural
correctness with many industry-standard tools. As with the other PSI formats, most of the
metadata in the TraML file are encoded with the use of controlled vocabulary (CV)
terms. These terms are all included in the PSI-MS CV, also used by mzML, mzIdentML,
and mzQuantML and actively maintained by the PSI Mass Spectrometry Standards
The proper use of CV terms can be validated with the PSI semantic validator (21), which
uses the TraML mapping file to ensure that certain terms are used where required and
that other terms are not used in semantically invalid locations in the document. An
implementation of this semantic validator framework parses a TraML document to ensure
well-formed XML that adheres to the XML schema definition (XSD) and also applies the
rules encoded in the TraML mapping file, along with the latest (online) version of the
CV, to ensure that all CV terms are properly used. There are currently two
implementations of a semantic validator as described below in the “implementations”
section. Links to all the auxiliary files that define the format are available at the official
public TraML web page (http://www.psidev.info/index.php?q=node/405) at the PSI web
The TraML schema is organized into ten major top-level sets of information (Figure 2),
each of which can contain several levels of dependent information. The sets are
numbered 1 through 10 in Figure 2, and are described in more detail here. Element 1,
<SourceFileList>, contains CV terms that allow the listing of one or more data files from
which the transitions contained in the current file are derived. Element 2, <CvList>, is a
required element containing a listing of the CVs referenced in the file. Note that, while
the PSI-MS CV must always be listed here because every valid TraML will contain terms
from this CV, additional CVs may be used to annotate the transition information in ways
that are not yet supported by the PSI MS CV. Element 3, <ContactList>, provides a
container to list one or more people involved in the generation, validation, and/or
optimization of the transitions contained in the current file. Element 4, <PublicationList>,
is a container for one or more publications from which the transitions are derived. An
entire file may be the complete set of transitions from a single publication, or a merged
transition set distilled from several publications into a single file with reference to the
source of the individual transitions.
Element 5, <InstrumentList>, provides a container for specifying one or more
instruments that can be referenced in the context of specifying validation and
optimization information for the transitions. Element 6, <SoftwareList>, provides a
container for describing software programs that were used to predict, validate, and/or
optimize the transitions contained in the current file. Apart from CvList, all of these
elements are optional, thus making it possible to encode very simple lists in TraML,
while still allowing the option of adding rich metadata.
Following these initial 6 metadata containers is element 7, <ProteinList>, an optional list
of protein identifiers that may be referenced by peptide entries. The protein entries may
have accession numbers, full names, or even full sequences. Following this is element 8,
<CompoundList>, which may contain any number of peptide or compound entries. A
„compound‟ is used here to represent a biomolecule that is more generic than a peptide,
allowing, for instance, the inclusion of chemical compounds and metabolites. These
peptide or compound elements are then referenced in the subsequent transition or target
Indeed, element 9, the <TransitionList> is encountered next. Unsurprisingly, this list
forms the heart of the document. Each transition must at minimum contain the barest of
information about the precursor and product m/z value, but may furthermore contain rich
information about interpretations, predictions, as well as instrument configurations on
which the transition has been tested or optimized. The transitions will typically reference
the previously listed peptides or compounds.
Figure 2. Schematic overview of the TraML schema. Each rectangle represents an
XML element with the displayed name. Optional elements are depicted with a
dashed outline. Elements can contain other dependent elements. Some of these
elements are partly expanded on the right side of the diagram. The top of a TraML
document contains general information about the contents of the document, and
then the lists of compounds, transitions, and targets follow.
Finally the optional element 10 is a general <TargetList> container, which may contain
an inclusion list and/or an exclusion list. Each of these lists contains individual targets
with at minimum a precursor m/z, but optionally also retention times and other attributes.
Although the format is primarily intended for the exchange of SRM transition lists, this
final component was added to manage and exchange of ordinary inclusion or exclusion
precursor m/z lists in product ion scans. It is expected that this is a relatively minor use
case, however it is envisaged in future iterations of mass spectrometers this will become a
major feature as whole proteome measurements will become more routine. There is no
other suitable format for encoding such information, so it was suggested late in
development that the format support this data type as well. It was considered to simply
make <Transition> a more generic element that could also contain inclusion targets, but
the working group decided that trying to force inclusion targets (with only a precursor
m/z) into a <Transition> element would only lead to validation difficulties, and that this
minor use case was therefore best left as a separate, optional component in the schema.
We expect TraML to be used in three primary ways: as an archival format, as an
exchange format, and as a working format. For example, it can be used as an archival
format to display supplementary material of journal articles. Currently, transition lists are
stored in tables of varying formats, sometimes even as PDF files, from which it can be
difficult to extract relevant data. If transitions are stored in an approved TraML format,
any TraML-supporting software will immediately be able to read such a file, encouraging
its reuse. Another important use will be for the general exchange of transition lists
between labs or lab members. When one wants to share a list, it is now commonplace to
send an Excel sheet of transitions, which must then often be adjusted to fit the workflow
of the destination. With the emergence of public repositories of experimentally validated
transitions for large numbers of proteins(10, 12, 14), we expect the need for efficient
transition file exchange to increase dramatically. The exchange of transition lists is
particularly important in the case of targeted proteomics as a set of transitions, once
optimized, can be used perpetually. The final intended use is as a working format.
Transition lists often need to undergo bulk modifications such as recalculation of
retention times for the local instrumental setup, or optimization for the local instrument or
specific instrument conditions, and we envision that the software tools that perform these
recalculations or enhancement can use TraML as a document that undergoes active
revision. It may be that individual software packages will continue to support their native
formats, but the reuse of lists will be greatly enhanced by the common use of a standard
As the development of the format has occurred under the PSI, the primary intended use
has been for proteomics experiments. However, the needs of metabolomics research,
where SRM techniques have been used for far longer, have been incorporated into the
format. The metadata associated with metabolomics experiments tends to be less complex
than that for proteomics since the whole complexity of peptide-protein mapping can be
excluded. This schema can also support similar targeted mass spectrometry for the SRM
application to lipidomics given that the application of this technique provides for a
similar common denominator of parent and transition mass tables. Instead of peptide
sequences and protein mappings, basic compositional information and database
accessions may be associated with targeted molecular compounds instead.
As noted above, the primary use case for this format is for targeted mass spectrometry
SRM assays, for which transitions requiring both precursor m/z and product m/z are the
key components. In addition, ordinary inclusion and exclusion lists are also supported for
current and future developments in whole proteome approaches. Such lists are often
employed to follow up on features detected in MS1 scans that have not yet been
identified or confirmed with MS2 scans. TraML supports both inclusion lists, specifying
which features to identify with fragmentation events, and exclusion lists, that specify
features not to select for fragmentation in a future run. Broad sharing of inclusion or
exclusion lists seems rare, but whole-proteome quantification via an inclusion list
containing the top proteotypic peptides for each protein has been shown to be
feasible(22) and may become a popular approach. In any case, the format can be used as
a working format where inclusion lists are iteratively developed and optimized during an
As a mechanism for supporting iterative workflows, various levels of confidence for a
transition can be encoded in TraML, with appropriate references to the history of
increasing confidence. Transitions can be marked as predicted based on some algorithm
or as selected from a real MS/MS spectrum, although perhaps from a different kind of
instrument. Transitions can be called “optimized” for a specific instrument model if they
are based on selection from an MS/MS spectrum or chromatogram acquired with that
instrument model, and “CE optimized” if the optimum collision energy is determined.
Finally, a transition can be called “verified” if chromatograms have been acquired and
minimal confusion with contaminating peaks is verified in the target sample. The history
of such an optimization workflow can be encoded in TraML, thereby giving researchers
who use the transitions the ability to assess the past history of the transitions.
An example of such an iterative workflow might occur as follows: a series of shotgun
experiments are analyzed to select detectable peptides for a list of relevant proteins to
create a list of candidate peptide and transition targets, and the resulting transitions
written in TraML with an annotation that the transitions are selected from ion trap data.
Synthetic peptides are acquired and the resulting peptides are measured via the candidate
transitions on an Agilent QQQ instrument; the resulting mzML files analyzed by
automated software and unsuitable transitions are discarded and a new, updated TraML
file is written with verification results added via <ValidationStatus> elements. Then a
collision energy optimization procedure is run to determine optimum energies for the
remaining transitions, and the results are written to an updated TraML file. Finally, the
selected transitions are monitored in a plasma sample to determine which transitions
show unacceptable interferences with other ions in this type of sample, and the TraML
file is again updated with new information in <ValidationStatus>. The final TraML file
represents an optimized set of transitions and the history of their development, and it can
be used to generate methods for the experiment assays and be submitted as supplemental
material with a manuscript as the final transitions used in the experiment, eventually to be
archived in public transition databases.
TraML is not intended to represent the results of an SRM experiment, but rather for use
as the input for an SRM experiment. The direct results of an SRM experiment in the form
of chromatograms can be stored in the mzML format. The quantitative measurements and
subsequent statistical aggregation can be stored in a format currently being developed by
the PSI, namely mzQuantML (http://www.psidev.info/index.php?q=node/457).
Implementations and examples
TraML has already become quite mature; it has gone through several rounds of revision
and refinement based on feedback from many experienced researchers from different
institutions. Furthermore, instrument and software vendors actively participate in PSI and
have been a part of the development of TraML. Most of the significant SRM-related
software tools either already support the format, or their authors participated in the
development of TraML with the intent to support the format soon.
There are already several existing software implementations of the TraML schema. This
is important for several reasons. First, it means that potential users do not need to write
their own software to begin using the format. Second, it is the act of implementing the
format, and reading and writing real data, that provides a real-world test of the
format(18). Finally, the existence of several software implementations prior to official
completion of TraML indicates the need for and interest in a standard format.
The ProteoWizard project(23) aims to provide an extensive reusable C++ library as well
as software applications for the analysis and manipulation of mass spectrometry data.
ProteoWizard is the reference implementation for mzML, and is distributed under a very
permissive Apache 2.0 license, which allows it to be incorporated in any other software
without constraints on the license of the final product. ProteoWizard now provides a set
of classes for the TraML elements as well as code to read and write TraML files into
The TraML schema has been implemented in an open-source Java library by the jTraML
toolkit(24), also under the Apache 2.0 license. It provides a complete API for all TraML
elements, along with syntactic and semantic validation support, and demonstrates the use
of these classes with an on-line converter that can transform a variety of existing tab-
separated-value formats to and from TraML, available at http://iomics.ugent.be/jtraml.
The OpenMS project (25) also provides a reusable set of C++ libraries for the processing
and analysis of mass spectrometry data made available under the GNU Lesser Public
License (LGPL). TraML support is built into the library, and tools are included for
manipulating transition lists. An on-line TraML semantic validator is hosted by an
OpenMS server (http://open-ms.sourceforge.net), and allows anyone to upload a TraML
file and verify the validity of the file.
Skyline(7) is a C# client application for Windows that enables very flexible and user-
friendly manipulation and maintenance of transition lists as well as chromatogram
analysis. It is built on top of the ProteoWizard libraries and could readily derive its
TraML support through ProteoWizard itself, although this has not yet been implemented.
The Automated Targeted And Quantitative System(8) (ATAQS) is a web-based
collaborative system for managing an entire targeted proteomics workflow from
beginning (protein and transition selection) to end (quantitative analysis of the
chromatograms). Transition lists may be imported, stored, manipulated, and exported
using ATAQS. Several formats, including TraML, are supported.
The SRMAtlas component(12) of the PeptideAtlas project (9-10) provides a publicly
accessible compendium of proteotypic peptides and transitions collated from several
sources and specific species builds. This includes both the PeptideAtlas Transitions
Resource (PATR), which stores curated lists of transitions collected from published
articles, as well as community submissions. These are available for download in the
native format and soon in the TraML format. Queries to the SRMAtlas compendium can
be returned in several formats, soon in TraML as well.
The MRMaid-DB resource does not yet support TraML, but the MRMaid-DB journal
article(14) indicates that TraML support will be forthcoming as soon as TraML is
declared stable. The authors compared the MRMaid-DB database data model to the
schema of an earlier development version of TraML and showed that TraML supports
nearly all of the fields and concepts in their database. The only exception was the storage
of coefficient of variance measures, which TraML now supports via a new controlled
The Anubis software (http://www.quantitativeproteomics.org/anubis) provides a system
for automated peptide quantification using SRM data. By its support for transition lists in
TraML format, as well as raw MS data in mzML format, it is an example of software that
can analyze data from all major instrument vendors through implementation of standards
Example TraML documents are available at the official TraML web page, including a
hand-crafted “ToyExample” document that demonstrates the use of most elements,
attributes, and CV terms. There are also examples of a real transition list for an SRM
yeast experiment generated by ATAQS and a yeast inclusion list generated by the
Proteios system(26-27), which supports TraML for inclusion/exclusion lists, as well as a
transition list converted by the jTraML toolkit.
We have developed the open TraML standard format for storage and exchange of SRM
transitions. Along with the format, we demonstrate several initial implementations across
the community, provide semantic validators and extensive documentation to ensure
proper implementation, and furnish multiple example files to demonstrate correct
implementations. Widespread use of TraML will facilitate the exchange of transitions,
reduce time spent handling incompatible list formats, increase the reusability of
previously optimized transitions, and thus accelerate the field of targeted proteomics via
SRM. The format provides for rich annotation of transition lists with an extensive set of
optional components. However, since these annotations are optional, very simple
transition lists may also be encoded in TraML.
The PSI is currently developing a module for the Minimum Information About a
Proteomics Experiment (MIAPE)(28) specification, called MIAPE-Quant. It specifies a
set of minimum information that should be provided when publishing a quantitative
proteomics experiment, including an SRM experiment. TraML will serve as the data
format that can encode the minimum information concepts in MIAPE-Quant related to
the input for a SRM experiment. All materials related to the TraML format are available
at the PSI web page for this format at http://www.psidev.info/index.php?q=node/405.
We thank the steering committee and the editors of the Proteomics Standards Initiative
for the provision of the document process and feedback on the specification documents,
as well as the numerous participants of the PSI Mass Spectrometry Standards Working
Group. We acknowledge the contributions of our colleague Andreas Bertsch, who lost his
life unexpectedly and far too early. This work has been funded in part by NIH with
NHLBI under contract N01-HV-28179, NIGMS grant GM087221, NHGRI grant
HG005805, EU FP7 grant 'ProteomeXchange' (grant number 260558), and the Systems
Biology Initiative of the State of Luxembourg.
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