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The emergence of RNA velocity has enriched our understanding of the dynamic transcriptional landscape within individual cells. In light of this breakthrough, we embarked on integrating RNA velocity with cellular pseudotime inference, aiming to improve the prediction of cell orders along biological trajectories beyond existing methods. Here, we developed LVPT, a novel method for pseudotime and trajectory inference. LVPT introduces a lazy probability to indicate the probability that the cell stays in the original state and calculates the transition matrix based on RNA velocity to provide the probability and direction of cell differentiation. LVPT shows better and comparable performance of pseudotime inference compared with other existing methods on both simulated datasets with different structures and real datasets. The validation results were consistent with prior knowledge, indicating that LVPT is an accurate and efficient method for pseudotime inference.
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http://dx.doi.org/10.3390/biom13081242 | DOI Listing |
Bioinformatics
September 2025
Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Motivation: RNA velocity has become a powerful tool for uncovering transcriptional dynamics in snapshot single-cell data. However, current RNA velocity approaches often assume constant transcriptional rates and treat genes independently with gene-specific times, which may introduce biases and deviate from biological realities. Here, we present InterVelo, a novel deep learning framework that simultaneously learns cellular pseudotime and RNA velocity.
View Article and Find Full Text PDFExp Cell Res
September 2025
Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China; Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, Guangdong 510080, China. Electronic address:
Background: Chronic rejection is a major cause of long-term kidney allograft failure, characterized by persistent inflammation and progressive fibrosis. Macrophages are central mediators of this process, but their phenotypic heterogeneity and regulatory mechanisms in chronic rejection remain incompletely understood.
Methods: We performed single-cell transcriptomic analysis on renal allograft biopsies from patients with different types of rejection and on a time-course rat model of chronic rejection.
NPJ Precis Oncol
September 2025
Shapingba Hospital affiliated to Chongqing University (Shapingba District People's Hospital of Chongqing), Shapingba District, Chongqing, China.
Hepatocellular carcinoma (HCC) is an aggressive and heterogeneous liver cancer with restricted therapy selections and poor diagnosis. Although there have been great advances in genomics, the molecular mechanisms essential to HCC progression are not yet fully implicit, particularly at the single-cell stage. This research utilized single-cell RNA sequencing technology to evaluate transcriptional heterogeneity, immune cell infiltration, and potential therapeutic targets in HCC.
View Article and Find Full Text PDFbioRxiv
August 2025
Instituto de Assistência Médica ao Servidor Público Estadual, Sao Paulo, SP, Brazil.
Here, we define cognitive resilience as slower or faster cognitive decline after we regress out the effects of common brain neuropathologies. Its understanding could provide important insights into the biology underlying cognitive health, enabling the development of more effective strategies to prevent cognitive decline and dementia. However, this requires the development of a practical method to quantify resilience and measure it in living individuals, as well as identifying heterogenous pathways associated with resilience in different individuals.
View Article and Find Full Text PDFHum Genomics
August 2025
Department of Cardiothoracic Surgery, The Fourth Affiliated Hospital of Soochow University, Suzhou, 215000, China.
Background: Mitotic catastrophe (MC) is a well-recognized endogenous mechanism of tumor cell death, characterized as a delayed cell death process associated with aberrant mitosis. However, its prognostic significance in the context of intratumoral heterogeneity in esophageal squamous cell carcinoma (ESCC) remains largely unexplored.
Methods: We performed an in-depth analysis of single-cell RNA sequencing (scRNA-seq) data from ESCC obtained from the Gene Expression Omnibus (GEO) database.