1 Department of Biology, Concordia University, 7141 Sherbrooke St. W., Montreal, QC, H4B 1R6, Canada.
2 Centre for Applied Synthetic Biology, Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St. W., Montreal, QC, H4B 1R6, Canada.
3 Canadian Centre for Computational Genomics (C3G), McGill University, 1010 Sherbrooke St. W. Suite 1800, Montreal, QC, H3A 2R7, Canada.
4 Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, 740 Dr Penfield Ave, Montreal, QC, H3A 0G1, Canada.
5 Institute of Computer Science, University of Tartu, Narva mnt 18, Tartu, 51009, Estonia.
6 Department of Human Genetics, McGill University, 3640 University, Room W 315 D, Montreal, QC, H3A 0C7, Canada.
7 Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
8 Rosalind & Morris Goodman Cancer Institute, McGill University, 1160 Pine Ave W, Montreal, QC, H3A 1A3, Canada.

Whole-genome duplication (WGD) events are common across various organisms; however, the retention and evolution of WGD paralogs is not fully understood. Quantitative measure of protein redistribution in response to the deletion of their WGD paralog provides insight into sources of gene retention. Here, we describe PARPAL (PARalog Protein Redistribution using Abundance and Localization in Yeast), a web database that houses results of high-content screening and deep learning neural network analysis of the redistribution of 164 proteins reflecting how their subcellular localization and protein abundance change in response to their paralog deletion in the budding yeast, Saccharomyces cerevisiae. We interrogated a total of 82 paralog pairs in two genetic backgrounds for a total of ~3,500 micrographs of ~460,000 cells. For example, Skn7-Hms2 exhibited dependent redistribution and Cue1-Cue4 showed compensatory redistribution response. PARPAL also links to other studies on trigenic interactions, protein-protein interactions and protein abundance. PARPAL is available at https://parpal.c3g-app.sd4h.ca and is a valuable resource for the yeast community interested in understanding the retention and evolution of paralogs and can help researchers to investigate protein dynamics of paralogs in other organisms.