A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions

Endometriosis is a common inflammatory
estrogen-dependent gynecological disorder, associated with pelvic pain and
reduced fertility in women. Several aspects of this disorder and its cellular
and molecular etiology remain unresolved. We have analyzed the global gene
expression patterns in the endometrium, peritoneum and in endometriosis lesions
of endometriosis patients and in the endometrium and peritoneum of healthy women.
In this report, we present the EndometDB, an interactive web-based user
interface for browsing the gene expression database of collected samples
without the need for computational skills. The current database incorporates
the expression data from 115 patients and 53 controls, with over 24000 genes
and clinical features, such as their age, disease stages, hormonal medication,
menstrual cycle phase, and the different endometriosis lesion types. Using the
web-tool, the end-user can easily generate various plot outputs, including
boxplots, heatmaps and scatterplots, and the generated plot outputs can be downloaded
in pdf-format. Availability
and implementation: The web-based user interface is implemented using HTML5,
JavaScript, CSS, Plotly and R. It is freely available from URL: https://endometdb.utu.fi/gene_analysis.

Endomet Database dump and schema.

Number of samples used in quantitative real-time PCR.

Pie chart showing the percentage of the different types of samples analyzed for global gene expression by microarrays.
Multidimensional scaling of WNT pathway genes of
the endometrium vs endometriosis samples using Canberra distance metric and
colored by tissues. The analysis separates endometrial specimens from
the different lesions.
Result of scree test for PCA analysis of WNT
pathway genes. The scree plot explains how much the principal components
account for the total variance in the expression data.