MRMPROBS project


Main program is available from here. MRMPROBS program.

The file converter is available from here. File converter.

MRM database is provided. MRM database.

Demonstration files and the library are downloadable from here. Demonstration files and library.

The tutorial is provided by English and Japanese.

Please cite

- Tsugawa et al (2014) MRMPROBS Suite for metablomics using large-scale MRM assays Bioinformatics, 30, 2379-2380 [Pubmed]

- Tsugawa et al (2013) MRMPROBS: A Data Assessment and Metabolite Identification Tool for Large-Scale Multiple Reaction Monitoring Based Widely Targeted Metabolomics Analytical Chemistry, 85, 5191-5199 [Pubmed]


Our objective is to develop a data analysis software for widely targeted metabolomics by means of triple quadrupole mass spectrometry (QqQ/MS). Although the strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability, software development for the data analysis of MRM transitions lags behind in metabolomics: data assessment usually relies on manual evaluation due to the lack of automated probabilistic measures. Manual verification of such large-scale MRM data sets is not only laborious, but often subjective, erroneous, and even irreproducible. Therefore, objective evaluation is needed to minimize misinterpretations of biological issues. To satisfy these requirements we developed a software program, MRMPROBS (Multiple Reaction Monitoring based PROBabilistic System for widely targeted metabolomics), written in C# language for widely targeted metabolomics. It evaluates the metabolite peaks by posterior probability, defined as the odds ratio by means of a newly optimized multivariate logistic regression model, and visualizes large-scale MRM data sets with user-friendly graphical user interfaces to allow data curation and statistical analyses. Our program offers the probability from the theoretical value based on MRM transition library and the prior distribution based on the analytical condition to the detected peaks.

Overview of MRMPROBS software

File converter

We currently utilize a freely available file format converter (offered from Reifycs Inc.) that converts raw data from each instrument to the Reifycs Analysis Base File (ABF) format.
We also support mzML file format converted by an open source file translator ProteoWizard . Data import from Waters(.raw) became possible indirectly via mzML.

Import .abf files(or .mzML files) and MRM transition library (compound library)

MRMPROBS imports ABF format files (.abf) from measured samples and the reference (i.e. MRM transition) library in the tab-delimited text format that contains the target compound name, retention time, target or qualifier, QT ratio (optional), and precursor and product m/z.
Edited in 14/3/31: The library format to deal with mzML files is slightly different from the original one. Please see our MRMPROBS manual.

Data processing

After ABF files and MRM transition library are imported, MRMPROBS detects and constructs the peak groups and calculates five scores (intensity-, retention time-, QT ratio-, shape-, and co-elution score) for each peak group by comparing the detected peak intensity, qualifier transition records, and reference information. Our peak detection method is based on the local maximum and local minimum of raw data points. Our software also accepts a peak group consisting of only one transition record. While this is not recommended, in such cases only two scores (the intensity- and the retention time score) are calculated. Then the probability is computed for each peak group by a multivariate regression model. The odds ratio is calculated as a posterior probability of a true peak given the five scores. A peak group of the highest probability is selected as a quantification value in the resulting data matrix. This process is repeated for all transition group records of all samples. The result can be manually confirmed and corrected as shown the below figure.


This program supports interpolation methods for missing values, normalization methods (internal standard, LOESS/Cubic-spline etc.), and principal component analysis.
Please also see our excel macro based statistical analysis tool page.

RIKEN Center for Sustainable Resource Science (formerly Plant Science Center)
Practical and Useful Data Analysis Tools for Metabolomics Research