Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), exhibits complex patterns of tissue-specific effects. Characterization of these patterns may allow us to better understand mechanisms of gene regulation and disease etiology. We develop a constrained matrix factorization model, sn-spMF, to learn patterns of tissue-sharing and apply it to 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors reflect tissues with known biological similarity and identify transcription factors that may mediate tissue-specific effects. sn-spMF, available at https://github.com/heyuan7676/ts_eQTLs , can be applied to learn biologically interpretable patterns of eQTL tissue-specificity and generate testable mechanistic hypotheses.
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http://dx.doi.org/10.1186/s13059-020-02129-6 | DOI Listing |
Biomedicines
January 2025
Major of Big Data Convergence, Division of Data Information Science, Pukyong National University, Busan 48513, Republic of Korea.
Over the past few decades, micro ribonucleic acids (miRNAs) have been shown to play significant roles in various biological processes, including disease incidence. Therefore, much effort has been devoted to discovering the pivotal roles of miRNAs in disease incidence to understand the underlying pathogenesis of human diseases. However, identifying miRNA-disease associations using biological experiments is inefficient in terms of cost and time.
View Article and Find Full Text PDFFoods
January 2025
Faculty of Technology and Metallurgy, University of Belgrade, 11120 Belgrade, Serbia.
A rapid and efficient ultrasound-assisted extraction (UAE) procedure followed by inductively coupled plasma mass spectrometry (ICP-MS) was developed for the determination of 14 rare earth elements (REEs) (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu), along with yttrium (Y) and scandium (Sc), in coffee samples. The method was validated using certified reference material (NIST SRM 1547), recovery tests at four fortification levels, and comparisons with microwave-assisted digestion (MAD). Excellent accuracy and precision were achieved, with recovery rates ranging from 80.
View Article and Find Full Text PDFMetabolites
January 2025
Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, Guangzhou 510642, China.
: The integration of microbiome and metabolome data could unveil profound insights into biological processes. However, widely used multi-omic data analyses often employ a stepwise mining approach, failing to harness the full potential of multi-omic datasets and leading to reduced detection accuracy. Synergistic analysis incorporating microbiome/metabolome data are essential for deeper understanding.
View Article and Find Full Text PDFHum Mov Sci
January 2025
Department of Sports Rehabilitation, Cheongju University, Republic of Korea. Electronic address:
This study investigated muscle synergies during squats, focusing on the individual variability in motor control strategies. Sixteen healthy young adults performed 20 squats at a consistent speed. Muscle synergies were extracted using non-negative matrix factorization, followed by k-means clustering and discriminant analysis to categorize similar muscle synergies.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Neurological Care Unit, The First Affiliated Hospital of YangTze University, Jingzhou, Hubei, China.
Background: Recent years have seen persistently poor prognoses for glioma patients. Therefore, exploring the molecular subtyping of gliomas, identifying novel prognostic biomarkers, and understanding the characteristics of their immune microenvironments are crucial for improving treatment strategies and patient outcomes.
Methods: We integrated glioma datasets from multiple sources, employing Non-negative Matrix Factorization (NMF) to cluster samples and filter for differentially expressed metabolic genes.
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