Transcription in ischemic stroke – reperfused mice – Transition database
Introduction
Stroke remains a leading cause of death and disabilities worldwide.
Furthermore, every fourth adult will be injured by stroke in their lifetime,
emphasizing the critical need for comprehensive research into its mechanisms and potential treatments.
Ischemic stroke is characterized by the abrupt interruption of cerebral blood flow and,
in particular, inflicts profound damage,
including cell death and intricate alterations within the brain's structure and function.
Here, we have investigated a murine (C57BL/6JR male mice) model of filament-induced ischemic stroke,
followed by spatial gene expression profiling (10X Genomics) at the acute phase (24 hours) of reperfusion.
Our database encompasses a comprehensive analysis of gene expression alterations,
with a specific focus on delineating the intricate responses driving stroke pathology and recovery.
Through this platform, we endeavor to provide valuable contributions to the complex interplay
between genetics and stroke pathology, ultimately contributing to developing novel therapeutic strategies.
Please cite the TRANSITION database as:
Citation will be updated.
Gene Summary
Differential expressed genes between the two hemispheres
* Wilcoxon Rank Sum test were used to identify differentially expressed genes between two groups of cells
* pct: The percentage of cells where the gene detected in the group
* avg_log2FC: log fold-chage of the average expression between the two groups.
* p_val_adj: Adjusted p-value, based on bonferroni correction using all genes in the dataset
Spot information / gene expression violin plot / box plot
In this tab, users can visualise the gene expression or continuous Spot information
(e.g. Number of UMIs / module score) across groups of Spots (e.g. libary / clusters).
Proportion / Spot numbers across different Spot information
In this tab, users can visualise the composition of single Spots based on one discrete
Spot information across another discrete Spot information.
Usage examples include the library or cellcycle composition across clusters.
In this tab, users can visualise the gene expression patterns of
multiple genes grouped by categorical Spot information (e.g. library / cluster).
The normalised expression are averaged, log-transformed and then plotted.