A1 Journal article – refereed

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




List of Authors: Gabriel M, Fey V, Heinosalo T, Adhikari P, Rytkönen K, Komulainen T, Huhtinen K, Laajala TD, Siitari H, Virkki A, Suvitie P, Kujari H, Aittokallio T, Perheentupa A, Poutanen M

Publication year: 2020

Journal: Scientific Data

Journal name in source: Scientific data

Journal acronym: Sci Data

Volume number: 7

Number of pages: 13

ISSN: 2052-4463

eISSN: 2052-4463

DOI: http://dx.doi.org/10.1038/s41597-020-00623-x


Abstract
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 EndometDB 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 and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format.Availability and implementationThe web-based user interface is implemented using HTML5, JavaScript, CSS, Plotly and R. It is freely available from https://endometdb.utu.fi/ .

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Last updated on 2021-24-06 at 11:46