Determining metabolomic differences among samples of different phenotypes is a critical
component of metabolomics research. With the rapid advances in analytical tools such as …

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few
therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a …

Feature-based molecular networking (FBMN) is a popular analysis approach for liquid
chromatography–tandem mass spectrometry-based non-targeted metabolomics data. While …

SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human
protein analytes in serum, plasma, and other biological matrices with high sensitivity and …

Quantile normalization is an important normalization technique commonly used in high-
dimensional data analysis. However, it is susceptible to class-effect proportion effects (the …

Preterm birth (PTB) is defined as the birth of an infant before 37 weeks of gestational age. It
is the leading cause of perinatal morbidity and mortality worldwide. In this study, we present …

Mass spectrometry-based proteomics plays a critical role in current biological and clinical
research. Technical issues like data integration, missing value imputation, batch effect …

Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic
feature for detecting the presence of cancer and determining its origin. The purpose of this …

Single-cell data integration can provide a comprehensive molecular view of cells, and many
algorithms have been developed to remove unwanted technical or biological variations and …

Objective High‐throughput gene expression profiling of tissue samples from patients with
systemic sclerosis (SS c) has identified 4 “intrinsic” gene expression subsets: inflammatory …