A review of matched-pairs feature selection methods for gene expression data analysis

S Liang, A Ma, S Yang, Y Wang, Q Ma - Computational and structural …, 2018 - Elsevier
With the rapid accumulation of gene expression data from various technologies, eg,
microarray, RNA-sequencing (RNA-seq), and single-cell RNA-seq, it is necessary to carry …

Gene–environment interaction: A variable selection perspective

F Zhou, J Ren, X Lu, S Ma, C Wu - Epistasis: Methods and Protocols, 2021 - Springer
Gene–environment interactions have important implications for elucidating the genetic basis
of complex diseases beyond the joint function of multiple genetic factors and their …

Causality-driven candidate identification for reliable DNA methylation biomarker discovery

X Tang, R Guo, Z Mo, W Fu, X Qian - Nature Communications, 2025 - nature.com
Despite vast data support in DNA methylation (DNAm) biomarker discovery to facilitate
health-care research, this field faces huge resource barriers due to preliminary unreliable …

Biomarker discovery study design for type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study

HS Lee, BR Burkhardt, W McLeod… - Diabetes/metabolism …, 2014 - Wiley Online Library
Abstract Aims The Environmental Determinants of Diabetes in the Young planned biomarker
discovery studies on longitudinal samples for persistent confirmed islet cell autoantibodies …

[HTML][HTML] Genetic Diversity and Genome-Wide Association Study of Seed Aspect Ratio Using a High-Density SNP Array in Peanut (Arachis hypogaea L.)

K Zou, KS Kim, K Kim, D Kang, YH Park, H Sun, BK Ha… - Genes, 2020 - mdpi.com
Peanut (Arachis hypogaea L.) is one of the important oil crops of the world. In this study, we
aimed to evaluate the genetic diversity of 384 peanut germplasms including 100 Korean …

Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm

M Avalos, H Pouyes, Y Grandvalet, L Orriols… - BMC …, 2015 - Springer
This paper considers the problem of estimation and variable selection for large high-
dimensional data (high number of predictors p and large sample size N, without excluding …

Incorporating genetic networks into case-control association studies with high-dimensional DNA methylation data

K Kim, H Sun - BMC bioinformatics, 2019 - Springer
Background In human genetic association studies with high-dimensional gene expression
data, it has been well known that statistical selection methods utilizing prior biological …

NEpiC: a network-assisted algorithm for epigenetic studies using mean and variance combined signals

P Ruan, J Shen, RM Santella, S Zhou… - Nucleic acids …, 2016 - academic.oup.com
DNA methylation plays an important role in many biological processes. Existing epigenome-
wide association studies (EWAS) have successfully identified aberrantly methylated genes …

Gene selection by incorporating genetic networks into case-control association studies

X Cao, X Liang, S Zhang, Q Sha - European Journal of Human Genetics, 2024 - nature.com
Large-scale genome-wide association studies (GWAS) have been successfully applied to a
wide range of genetic variants underlying complex diseases. The network-based regression …

pETM: a penalized Exponential Tilt Model for analysis of correlated high-dimensional DNA methylation data

H Sun, Y Wang, Y Chen, Y Li, S Wang - Bioinformatics, 2017 - academic.oup.com
Motivation DNA methylation plays an important role in many biological processes and
cancer progression. Recent studies have found that there are also differences in methylation …