WaveICA 2.0: a novel batch effect removal method for untargeted metabolomics data without using batch information

MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics

(2020) Zhiqiang Pang et al.   Metabolites

WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis

(2019) Kui Deng et al.   ANALYTICA CHIMICA ACTA

Why Batch Effects Matter in Omics Data, and How to Avoid Them

(2017) Wilson Wen Bin Goh et al.   TRENDS IN BIOTECHNOLOGY

Normalization and integration of large-scale metabolomics data using support vector regression

(2016) Xiaotao Shen et al.   Metabolomics

Emerging applications of metabolomics in drug discovery and precision medicine

(2016) David S. Wishart   NATURE REVIEWS DRUG DISCOVERY

Intra-batch effect correction in liquid chromatography-mass spectrometry using quality control samples and support vector regression (QC-SVRC)

(2015) Julia Kuligowski et al.   ANALYST

Normalizing and Integrating Metabolomics Data

(2012) Alysha M. De Livera et al.   ANALYTICAL CHEMISTRY

Batch effect removal methods for microarray gene expression data integration: a survey

(2012) C. Lazar et al.   BRIEFINGS IN BIOINFORMATICS

CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets

(2011) Carsten Kuhl et al.   ANALYTICAL CHEMISTRY

Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry

(2011) Warwick B Dunn et al.   Nature Protocols

Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models

(2010) Simon N. Wood   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY