One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks.
Anal Chem
; 89(17): 8696-8703, 2017 09 05.
Article
em En
| MEDLINE
| ID: mdl-28752754
ABSTRACT
False positive and false negative peaks detected from extracted ion chromatograms (EIC) are an urgent problem with existing software packages that preprocess untargeted liquid or gas chromatography-mass spectrometry metabolomics data because they can translate downstream into spurious or missing compound identifications. We have developed new algorithms that carry out the sequential construction of EICs and detection of EIC peaks. We compare the new algorithms to two popular software packages XCMS and MZmine 2 and present evidence that these new algorithms detect significantly fewer false positives. Regarding the detection of compounds known to be present in the data, the new algorithms perform at least as well as XCMS and MZmine 2. Furthermore, we present evidence that mass tolerance in m/z should be favored rather than mass tolerance in ppm in the process of constructing EICs. The mass tolerance parameter plays a critical role in the EIC construction process and can have immense impact on the detection of EIC peaks.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Espectrometria de Massas
/
Algoritmos
/
Software
/
Cromatografia Líquida
/
Metabolômica
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Revista:
Anal Chem
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Estados Unidos