ArticleNature communications2021
Genoppi is an open-source software for robust and standardized integration of proteomic and genetic data.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 28 citations in OpenAlex.
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- C9ORF72 poly-PR disrupts expression of ALS/FTD-implicated STMN2 through SRSF7.Acta neuropathologica communications · 2025Article
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- Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease.Communications biology · 2024Article
- Antibiofilm and Antivirulence Properties of 6-Polyaminosteroid Derivatives against Antibiotic-Resistant Bacteria.Antibiotics (Basel, Switzerland) · 2023Article
- Systematic differences in discovery of genetic effects on gene expression and complex traits.Nature genetics · 2023Article
- Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia.iScience · 2023Article
- Protein interaction studies in human induced neurons indicate convergent biology underlying autism spectrum disorders.Cell genomics · 2023Article
- Outlining cardiac ion channel protein interactors and their signature in the human electrocardiogram.Nature cardiovascular research · 2023Article
- Challenges and opportunities for precision medicine in neurodevelopmental disorders.Advanced drug delivery reviews · 2022Review
- Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms.Neurobiology of disease · 2022Review
- Genoppi is an open-source software for robust and standardized integration of proteomic and genetic data.Nature communications · 2021Article
- Mind the translational gap: using iPS cell models to bridge from genetic discoveries to perturbed pathways and therapeutic targets.Molecular autism · 2021Review
Corrections and comments
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Authors and funding
10 authors at 1 institution in 3 countries.
Funding
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.
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