TY - JOUR
T1 - MRMPROBS
T2 - A data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics
AU - Tsugawa, Hiroshi
AU - Arita, Masanori
AU - Kanazawa, Mitsuhiro
AU - Ogiwara, Atsushi
AU - Bamba, Takeshi
AU - Fukusaki, Eiichiro
PY - 2013/5/21
Y1 - 2013/5/21
N2 - We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work. Our program overcomes these problems by detecting and identifying metabolites automatically, by separating isomeric metabolites, and by removing background noise using a probabilistic score defined as the odds ratio from an optimized multivariate logistic regression model. Our software program also provides a user-friendly graphical interface to curate and organize data matrices and to apply principal component analyses and statistical tests. For a demonstration, we conducted a widely targeted metabolome analysis (152 metabolites) of propagating Saccharomyces cerevisiae measured at 15 time points by gas and liquid chromatography coupled to triple quadrupole mass spectrometry. MRMPROBS is a useful and practical tool for the assessment of large-scale MRM data available to any instrument or any experimental condition.
AB - We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work. Our program overcomes these problems by detecting and identifying metabolites automatically, by separating isomeric metabolites, and by removing background noise using a probabilistic score defined as the odds ratio from an optimized multivariate logistic regression model. Our software program also provides a user-friendly graphical interface to curate and organize data matrices and to apply principal component analyses and statistical tests. For a demonstration, we conducted a widely targeted metabolome analysis (152 metabolites) of propagating Saccharomyces cerevisiae measured at 15 time points by gas and liquid chromatography coupled to triple quadrupole mass spectrometry. MRMPROBS is a useful and practical tool for the assessment of large-scale MRM data available to any instrument or any experimental condition.
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U2 - 10.1021/ac400515s
DO - 10.1021/ac400515s
M3 - Article
C2 - 23581547
AN - SCOPUS:84878274712
SN - 0003-2700
VL - 85
SP - 5191
EP - 5199
JO - Analytical Chemistry
JF - Analytical Chemistry
IS - 10
ER -