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Based on 337 human kidney and plasma samples, the authors generate the first kidney pQTL dataset and explore novel risk loci that are relevant for cardio-kidney-metabolic health.
Deep phenotyping of an ancestrally diverse group of 13,000 individuals in the Human Phenotype Project highlights diversity and variations in lifestyle factors, clinical features and molecular signatures of health and disease.
A large single-cell transcriptomic-based reference model for hematopoietic stem and progenitor cells from 148 age- and sex-diverse individuals identifies physiological and disease-specific changes across the lifespan, with potential diagnostic use for myelodysplastic syndromes.
Multi-omic single-cell and spatial analyses of lung cancer brain metastases from multiple cohorts identify high levels of chromosomal instability and a neural-like profile in brain metastases compared with primary tumors.
A single-cell study integrating data from lung tissues from patients with fatal COVID-19 from Malawi, the United States and Europe identifies shared and distinct immune and inflammatory mechanisms of response.
Incorporating a series of analytical steps, from data extraction and quality control to the generation of low-dimensional representations and to longitudinal analyses, an open-source software is proposed to standardize current electronic health record data processing and analysis pipelines.
A single-cell transcriptomic study from the Human Cell Atlas integrating over 11 million brain cells from 70 studies uncovers differences across human brain regions and identifies rare progenitor and microglia subtypes.
SteatoSITE is an open resource that integrates histopathologic assessments, transcriptomic data and longitudinal electronic health records for a cohort of 940 patients with metabolic dysfunction-associated steatotic liver disease.
A single-cell atlas of the human lungs, integrating data from 2.4 million cells from 486 individuals and including samples from healthy and diseased lungs, provides a roadmap for the generation of organ-scale cell atlases.
A single-cell analysis of tumor-infiltrating T cells from 16 cancer types identifies new T cell subsets and a stress response cell state enriched in tumors resistant to immunotherapy.
A large, publicly available dataset integrating RNA, whole-exome, T cell receptor and 16S rRNA sequencing from patients with colon cancer enables the discovery of a prognostic score consisting of tumor, immune and microbial features.
A set of ready-to-use tools for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq facilitates the implementation of single-cell technologies in clinical settings and the construction of single-cell tumor atlases.
Large-scale, comprehensive proteomic profiling of Alzheimer’s disease brain and cerebrospinal fluid reveals disease-associated protein coexpression modules and highlights the importance of glia and energy metabolism in disease pathogenesis.
Genetically engineered mouse models representing the spectrum of human cutaneous melanoma provide a platform for studying clinical responses to immunotherapy.
A comprehensive biobank of bacterial isolates with longitudinal and multi-omics characterization will advance understanding of the diversity and functions of human gut bacteria.
Systematic metabolite profiling across cancer cell lines uncovers patterns associated with genetic and epigenetic features and reveals dysregulated metabolic states that can be exploited for anticancer therapy
A biobank of ovarian cancer organoids recapitulates the histopathological and molecular hallmarks of patient tumors and provides a resource for preclinical research.
