RT Journal Article
SR Electronic
T1 Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.05.04.076034
DO 10.1101/2020.05.04.076034
A1 Greta Pintacuda
A1 Frederik H. Lassen
A1 Yu-Han H. Hsu
A1 April Kim
A1 Jacqueline M. Martín
A1 Edyta Malolepsza
A1 Justin K. Lim
A1 Nadine Fornelos
A1 Kevin C. Eggan
A1 Kasper Lage
YR 2020
UL http://biorxiv.org/content/early/2020/05/05/2020.05.04.076034.abstract
AB Combining genetic and cell-type-specific proteomic datasets can lead to new 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 that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We used Genoppi to analyze sixteen cell-type-specific protein interaction datasets of four proteins (TDP-43, MDM2, PTEN, and BCL2) 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 and one human iPSC-derived neuronal 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 neurodevelopmental and neurodegenerative diseases. Importantly, our analyses indicate that human iPSC-derived neurons are a relevant model system for studying the involvement of TDP-43 and BCL2 in amyotrophic lateral sclerosis.Competing Interest StatementThe authors have declared no competing interest.