Section: New Software and Platforms

WellFARE

Keywords: Bioinformatics - Statistics - Data visualization - Data modeling

Scientific Description: WellFARE is a Python library implementing linear inversion methods for the reconstruction of gene expression profiles from fluorescent or luminescent reporter gene data. WellFARE form the computational core of the WellInverter web application.

Functional Description: As input, WellFARE reads the primary data file produced by a 96-well microplate reader, containing time-series measurements of the absorbance (optical density) as well as the fluorescence and luminescence intensities in each well (if available). Various functions exist to analyze the data, in particular for detecting outliers, subtracting background, estimating growth rates, promoter activities and protein concentrations, visualizing expression profiles, synchronizing replicate profiles, etc. WellFARE is the computational core of the web application WellInverter.

News Of The Year: Publication in BMC Bioinformatics describing the new version of WellFARE

• Participants: Delphine Ropers, Hans Geiselmann, Hidde de Jong, Michel Page, Valentin Zulkower and Yannick Martin

• Partner: UGA

• Contact: Hidde de Jong

• Publication: Robust reconstruction of gene expression profiles from reporter gene data using linear inversion

• URL: https://github.com/ibis-inria/wellfare