Sammanfattning

A strategy for optimizing LC-MS metabolomics data processing is proposed. We applied this strategy on the XCMS open source package written in R on both human and plant biology data. The strategy is a sequential design of experiments (DoE) based on a dilution series from a pooled sample and a measure of correlation between diluted concentrations and integrated peak areas. The reliability index metric, used to define peak quality, simultaneously favors reliable peaks and disfavors unreliable peaks using a weighted ratio between peaks with high and low response linearity. DoE optimization resulted in the case studies in more than 57% improvement in the reliability index compared to the use of the default settings. The proposed strategy can be applied to any other data processing software involving parameters to be tuned, e.g., MZmine 2. It can also be fully automated and used as a module in a complete metabolomics data processing pipeline.

Publicerad i

Analytical Chemistry
2012, Volym: 84, nummer: 15, sidor: 6869-6876
Utgivare: AMER CHEMICAL SOC

SLU författare

• Moritz, Thomas

  • Institutionen för skoglig genetik och växtfysiologi, Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Analytisk kemi


Publikationens identifierare

DOI: https://doi.org/10.1021/ac301482k

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/42596