Citation
Please cite the following article when using statTarget or QC-RFSC algorithm:
Luan H., Ji F., Chen Y., Cai Z. (2018) statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data. Analytica Chimica Acta. dio: https://doi.org/10.1016/j.aca.2018.08.002
Luan H., Ji F., Chen Y., Cai Z. (2018) Quality control-based signal drift correction and interpretations of metabolomics/proteomics data using random forest regression. bioRxiv 253583; doi: https://doi.org/10.1101/253583
2017
1 NOREVA: normalization and evaluation of MS-based metabolomics data. Nucleic Acids Res 2017 gkx449. doi: 10.1093/nar/gkx449
2 Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges. Trends in Endocrinology & Metabolism 2017 doi: dx.doi.org/10.1016/j.tem.2017.07.001
3 Review of emerging metabolomic tools and resources: 2015–2016. ELECTROPHORESIS 2017 doi: 10.1002/elps.201700110
4 NormalizeMets: Analysis of Metabolomics Data. R package 2017