The Male Fertility Gene Atlas - A web tool for collecting and integrating data about epi-/genetic causes of male infertility [article]

Henrike Krenz, Jörg Gromoll, Thomas Darde, Fred Chalmel, Martin Dugas, Frank Tüttelmann
2020 medRxiv   pre-print
Interconnecting results of previous OMICs studies is of major importance for identifying novel underlying causes of male infertility. To date, information can be accessed mainly through literature search engines and raw data repositories. However, both have limited capacity in identifying relevant publications based on aggregated research results e.g. genes mentioned in images and supplements. To address this gap, we present the Male Fertility Gene Atlas (MFGA), a web tool that enables
more » ... at enables standardised representation and search of aggregated result data of scientific publications. An advanced search function is provided for querying research results based on study conditions/phenotypes, meta information and genes returning the exact tables and figures from the publications fitting the search request as well as a list of most frequently investigated genes. As basic prerequisite, a flexible data model that can accommodate and structure a very broad range of meta information, data tables and images was designed and implemented for the system. The first version of the system is published at the URL and contains a set of 46 representative publications. Currently, study data for 28 different tissue types, 32 different cell types and 20 conditions is available. Also, ~5,000 distinct genes have been found to be mentioned in at least ten of the publications. As a result, the MFGA is a valuable addition to available tools for research on the epi-/genetics of male infertility. The MFGA enables a more targeted search and interpretation of OMICs data on male infertility and germ cells in the context of relevant publications. Moreover, its capacity for aggregation allows for meta-analyses and data mining with the potential to reveal novel insights into male infertility based on available data.
doi:10.1101/2020.02.10.20021790 fatcat:emmyklfzufg3dij3t3euxy4ghi