Genoppi is an open-source software for robust and standardized integration of proteomic and genetic data.

Autor: Pintacuda G; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA., Lassen FH; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK., Hsu YH; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA., Kim A; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA., Martín JM; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA., Malolepsza E; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA., Lim JK; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.; Massachusetts Institute of Technology, Cambridge, MA, USA., Fornelos N; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA., Eggan KC; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA. eggan@mcb.harvard.edu.; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. eggan@mcb.harvard.edu., Lage K; Stanley Center at Broad Institute of MIT and Harvard, Cambridge, MA, USA. lage.kasper@mgh.harvard.edu.; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA. lage.kasper@mgh.harvard.edu.; Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark. lage.kasper@mgh.harvard.edu.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2021 May 10; Vol. 12 (1), pp. 2580. Date of Electronic Publication: 2021 May 10.
DOI: 10.1038/s41467-021-22648-5
Abstrakt: Combining genetic and cell-type-specific proteomic datasets can generate biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi (lagelab.org/genoppi) that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We use Genoppi to analyze 16 cell-type-specific protein interaction datasets of four proteins (BCL2, TDP-43, MDM2, PTEN) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer cell types and one human iPSC-derived neuronal cell type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodegenerative diseases. Importantly, our analyses suggest that human iPSC-derived neurons are a relevant model system for studying the involvement of BCL2 and TDP-43 in amyotrophic lateral sclerosis.
Databáze: MEDLINE
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