Abstract：
:The human interactome is instrumental in the systems-level study of the cell and the contextualization of disease-associated gene perturbations. However, reference organismal interactomes do not capture the cell-type-specific context in which proteins and modules preferentially act. Here, we introduce SCINET, a computational framework that reconstructs an ensemble of cell-type-specific interactomes by integrating a global, context-independent reference interactome with a single-cell gene-expression profile. SCINET addresses technical challenges of single-cell data by robustly imputing, transforming, and normalizing the initially noisy and sparse expression of data. Inferred cell-level gene interaction probabilities and group-level interaction strengths define cell-type-specific interactomes. We use SCINET to reconstruct and analyze interactomes of the major human brain and immune cell types, revealing specificity and modularity of perturbations associated with neurodegenerative, neuropsychiatric, and autoimmune disorders. We report cell-type interactomes for brain and immune cell types, together with the SCINET package.
journal_name
Cell Systjournal_title
Cell systemsauthors
Mohammadi S,Davila-Velderrain J,Kellis Mdoi
10.1016/j.cels.2019.10.007subject
Has Abstractpub_date
2019-12-18 00:00:00pages
559-568.e4issue
6eissn
2405-4712issn
2405-4720pii
S2405-4712(19)30383-7journal_volume
9pub_type
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