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Genome-wide association analyses identify 93 risk loci for venous thromboembolism (VTE). A polygenic score derived from these results identifies individuals at increased VTE risk equivalent to monogenic forms of the disease.
De novo genome assembly and analyses of 12 maize FILs provide insights into genomic and phenotypic differentiation of various heterotic groups and the molecular basis of heterosis in maize.
Genome-wide association studies comprising 1,091 metabolites and 309 metabolite ratios in 8,299 individuals from the Canadian Longitudinal Study on Aging provide insights into the genetic architecture of metabolites and their role in human diseases.
A single-cell massively parallel reporter assay is used to compare cis-regulatory sequence activities in cell line models and mouse retinal tissue ex vivo, identifying cell state- and cell-type-specific effects of sequence variation.
This Brain Somatic Mosaicism Network analysis of 283 cases of malformations of cortical development identifies 69 candidate and known genes in 76 patients. Single-nucleus RNA sequencing and mouse modeling implicate radial glia and daughter excitatory neurons.
SpiceMix uses latent variable modeling to infer cell identities by jointly analyzing intrinsic and spatial factors, allowing the identification of spatially variable metagenes and refined cell subtypes.
A single-cell transcriptomic analysis of endometriosis, endometriomas, eutopic endometrial samples and uninvolved ovary tissues highlights cell populations characteristic of these tissue types. Transcriptional and cellular heterogeneity across tissues suggests novel therapeutic targets and biomarkers for this disease.
High-quality multimodal single-cell, bulk and spatial genomics data are prepared from low-input, frozen needle biopsy specimens collected during routine clinical procedures.
DeepNeo identifies major histocompatibility complex (MHC) I or MHC II neoepitopes that are immunogenically compatible with the T cell repertoire. It can predict neoepitopes most likely to be depleted through spontaneous immunity or through immune checkpoint blockade from untreated and immunotherapy-treated tumor datasets.
The PATAT model is used to simulate SARS-CoV-2 epidemics in low- and middle-income countries, finding that diagnostic testing rates and proportions of viruses sequenced underpin timely and accurate novel variant virus detection.