SCORCH - sporedata/researchdesigneR GitHub Wiki

General description

The NIDA-backed Single Cell Opioid Responses in the Context of HIV (SCORCH) program was initiated in 2020 to create resources for detailed tissue analysis at the single-cell level. This includes producing single-nucleus transcriptomic data to identify new rare cell types and enrich crucial cellular groups, enhancing the understanding of the CNS impacts of Substance Use Disorder (SUD) and HIV. SCORCH is a collaborative project involving multidisciplinary teams from ten institutions: Yale, Boston University, Mount Sinai, the University of Nebraska Medical Center, the Broad Institute, University of California San Diego, Weill Cornell Medicine, The Allen Institute, Scripps Research, and a Data Coordination Center (DCC) based at the Institute for Genome Sciences at the University of Maryland Baltimore School of Medicine.

The SCORCH program established a data coordination, analysis, and scientific outreach center to manage and disseminate single-cell molecular data related to HIV/SUD. This center ensures that the data adheres to the FAIR principles (Findable, Accessible, Interoperable, Reusable), and it integrates additional molecular HIV/SUD datasets produced by NIDA-funded researchers to enhance their scientific utility. The SCORCH Data Center is designed to synergize with the knowledge and resources from other single-cell initiatives like BICCN and HuBMAP, aiming to deepen scientific insights. The harmonized molecular and single-cell HIV/SUD datasets will support immediate data mining by researchers to identify HIV and/or SUD biomarkers and potential therapeutic pathways. Additionally, the SCORCH Data Center will facilitate future analysis of these datasets as new and advanced data science and IT methods emerge, thereby optimizing the value of NIDA’s investment in data generation.

Related publications

• HIV integration in the human brain is linked to microglial activation and 3D genome remodeling
• Filgotinib suppresses HIV-1-driven gene transcription by inhibiting HIV-1 splicing and T cell activation
• The Clonal Expansion Dynamics of the HIV-1 Reservoir: Mechanisms of Integration Site-Dependent Proliferation and HIV-1 Persistence
• Morphine suppresses peripheral responses and transforms brain myeloid gene expression to favor neuropathogenesis in SIV infection
• HIV integration in the human brain is linked to microglial activation and 3D genome remodeling
• Detection of differentially abundant cell subpopulations in scRNA-seq data
• Computation and visualization of cell-cell signaling topologies in single-cell systems data using Connectome
• Zero-preserving imputation of single-cell RNA-seq data
• Forest Fire Clustering for single-cell sequencing combines iterative label propagation with parallelized Monte Carlo simulations
• Graph of graphs analysis for multiplexed data with application to imaging mass cytometry
• Spectral neighbor joining for reconstruction of latent tree Models
• Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise
• An accessible and versatile deep learning-based sleep stage classifier
• Molecular and cellular evolution of the primate dorsolateral prefrontal cortex
• Shock-and-kill versus block-and-lock: Targeting the fluctuating and heterogeneous HIV-1 gene expression

Data access

More information about SCORCH can be found at https://scorch.igs.umaryland.edu/

To access SCORCH data, visit https://scorch.igs.umaryland.edu/data-and-protocols.php