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Highly effective batch effect correction method for RNA-seq count data.
Comput Struct Biotechnol J
December 2024
Department of Computer Science and Information Science, California State University San Marcos, 333 S. Twin Oaks Valley Rd, San Marcos, CA 92096, USA.
RNA sequencing (RNA-seq) has become a cornerstone of transcriptomics, providing detailed insights into gene expression across diverse biological conditions and sample types. However, RNA-seq data are often confounded by batch effects, systematic non-biological variations that compromise data reliability and obscure true biological differences. To address these challenges, we introduce ComBat-ref, a refined batch effect correction method designed to enhance the statistical power and reliability of differential expression analysis in RNA-seq data.
View Article and Find Full Text PDFSemblans: Automated assembly and processing of RNA-Seq data.
Bioinformatics
January 2025
Department of Biological Sciences, University of Illinois at Chicago, Illinois 60607, United States.
Motivation: Recent advancements in parallel sequencing methods have precipitated a surge in publicly available short-read sequence data. This has encouraged the development of novel computational tools for the de novo assembly of transcriptomes from RNA-seq data. Despite the availability of these tools, performing an end-to-end transcriptome assembly remains a programmatically involved task necessitating familiarity with best practices.
View Article and Find Full Text PDFConstruction of a Dataset for All Expressed Transcripts for Alzheimer's Disease Research.
Brain Sci
November 2024
Systems Biology Lab for Metabolic Reprogramming, Department of Human Genetics and Cell Biology, School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China.
Accurate identification and functional annotation of splicing isoforms and non-coding RNAs (lncRNAs), alongside full-length protein-encoding transcripts, are critical for understanding gene (mis)regulation and metabolic reprogramming in Alzheimer's disease (AD). This study aims to provide a comprehensive and accurate transcriptome resource to improve existing AD transcript databases. : Gene mis-regulation and metabolic reprogramming play a key role in AD, yet existing transcript databases lack accurate and comprehensive identification of splicing isoforms and lncRNAs.
View Article and Find Full Text PDFCorrection of aberrant splicing of ELP1 pre-mRNA by kinetin derivatives - A structure activity relationship study.
Eur J Med Chem
December 2024
Laboratory of Experimental Biology, Faculty of Science, Palacký University, Šlechtitelů 27, CZ-78371 Olomouc, Czech Republic; Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University, Hněvotínská 3, 775 15 Olomouc, Czech Republic. Electronic address:
Familial dysautonomia is a debilitating congenital neurodegenerative disorder with no causative therapy. It is caused by a homozygous mutation in ELP1 gene, resulting in the production of the transcript lacking exon 20. The compounds studied as potential treatments include the clinical candidate kinetin, a plant hormone from the cytokinin family.
View Article and Find Full Text PDFDevelopment of machine learning models for diagnostic biomarker identification and immune cell infiltration analysis in PCOS.
J Ovarian Res
January 2025
Reproductive Medicine Center, Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age. It is characterized by symptoms such as hyperandrogenemia, oligo or anovulation and polycystic ovarian, significantly impacting quality of life. However, the practical implementation of machine learning (ML) in PCOS diagnosis is hindered by the limitations related to data size and algorithmic models.
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