Single-cell RNA-seq methods to interrogate virus-host interactions
The twenty-first century has seen the emergence of many epidemic and pandemic viruses,
with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate …
with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate …
[HTML][HTML] Deep learning applications in single-cell genomics and transcriptomics data analysis
Traditional bulk sequencing methods are limited to measuring the average signal in a group
of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution …
of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution …
Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
RNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in
snapshot single-cell data; however, current approaches for estimating RNA velocity lack …
snapshot single-cell data; however, current approaches for estimating RNA velocity lack …
Spatial transition tensor of single cells
Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal
information for cell states and transitions. The current lineage-inference methods either lack …
information for cell states and transitions. The current lineage-inference methods either lack …
Inference of high-resolution trajectories in single-cell RNA-seq data by using RNA velocity
Trajectory inference (TI) methods infer cell developmental trajectory from single-cell RNA
sequencing data. Current TI methods can be categorized into those using RNA velocity …
sequencing data. Current TI methods can be categorized into those using RNA velocity …
Spatiotemporal transcriptomic mapping of regenerative inflammation in skeletal muscle reveals a dynamic multilayered tissue architecture
Tissue regeneration is orchestrated by macrophages that clear damaged cells and promote
regenerative inflammation. How macrophages spatially adapt and diversify their functions to …
regenerative inflammation. How macrophages spatially adapt and diversify their functions to …
Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction
Background Current methods for analyzing single-cell datasets have relied primarily on
static gene expression measurements to characterize the molecular state of individual cells …
static gene expression measurements to characterize the molecular state of individual cells …
TFvelo: gene regulation inspired RNA velocity estimation
RNA velocity is closely related with cell fate and is an important indicator for the prediction of
cell states with elegant physical explanation derived from single-cell RNA-seq data. Most …
cell states with elegant physical explanation derived from single-cell RNA-seq data. Most …
[HTML][HTML] Unlocking biological insights from differentially expressed Genes: Concepts, methods, and future perspectives
H Yin, H Duo, S Li, D Qin, L Xie, Y Xiao, J Sun… - Journal of Advanced …, 2024 - Elsevier
Background Identifying differentially expressed genes (DEGs) is a core task of transcriptome
analysis, as DEGs can reveal the molecular mechanisms underlying biological processes …
analysis, as DEGs can reveal the molecular mechanisms underlying biological processes …