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


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Article Info

DATE

2021-05-10

AUTHORS

Greta Pintacuda, Frederik H. Lassen, Yu-Han H. Hsu, April Kim, Jacqueline M. Martín, Edyta Malolepsza, Justin K. Lim, Nadine Fornelos, Kevin C. Eggan, Kasper Lage

ABSTRACT

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. More... »

PAGES

2580

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-021-22648-5

    DOI

    http://dx.doi.org/10.1038/s41467-021-22648-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1137882771

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/33972534


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