KIAA0825
KIAA0825
Pharos Class
Tdark
RNA Expression
The results shown on this page are derived from a harmonized RNA-seq analysis of post-mortem brains from AD cases and controls. The samples were obtained from three human cohort studies across a total of nine different brain regions.
Overall Expression of KIAA0825 Across Brain Regions
This plot depicts the median expression of the selected gene across brain regions, as measured by RNA-seq read counts per million (CPM) reads. Meaningful expression is considered to be a log2 CPM greater than log2(5), depicted by the red line in the plot.
Filter the following charts by statistical model
Differential Expression of KIAA0825 Across Brain Regions
After selecting a statistical model, you will be able to see whether the selected gene is differentially expressed between AD cases and controls. The box plot depicts how the differential expression of the selected gene of interest (purple dot) compares with expression of other genes in a given tissue. Summary statistics for each tissue can be viewed by hovering over the purple dots. Meaningful differential expression is considered to be a log2 fold change value greater than 0.263, or less than -0.263.
Consistency of Change in Expression
This forest plot indicates the estimate of the log fold change with 95% confidence interval across the brain regions in the model chosen using the filter above. Genes that show consistent patterns of differential expression will have similar log-fold change value across brain regions.
Correlation of KIAA0825 with Hallmarks of AD
This plot depicts the association between expression levels of the selected gene in the DLPFC and three phenotypic measures of AD. An odds ratio > 1 indicates a positive correlation and an odds ratio < 1 indicates a negative correlation. Statistical significance and summary statistics for each phenotype can be viewed by hovering over the dots.
Similarly Expressed Genes
The network diagram below is based on a coexpression network analysis of RNA-seq data from AD cases and controls. The network analysis uses an ensemble methodology to identify genes that show similar coexpression across individuals.
The color of the edges and nodes indicates how frequently significant coexpression was identified. Each node represents a different gene and the amount of edges within the network. Darker edges represent coexpression in more brain regions.