A multimodal atlas of human brain cell types_2021 data
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PROVIDER: PRJNA781341 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A multimodal atlas of human brain cell types_2021 data
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Project description:A multimodal atlas of human brain cell types
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Project description:A multimodal atlas of human brain cell types
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Project description:<p>"A multimodal atlas of human brain cell types" includes sample data targeting two cell types that show species differences between mouse and human. First, it includes a detailed transcriptomic, morphological, and electrophysiological characterization of cell types in layer 1 of human middle temporal gyrus, focusing primarily on different inhibitory cell types. This project also includes gene expression data collected from nuclei in layer 5 of human fronto-insula, with a goal of identifying transcriptomic signatures of Von Economo neurons. Control samples collected as part of the same experiment are also included in the data set.</p> <p>This study was conducted as part of a collaboration between the Allen Institute for Brain Science, the University of Szeged, and the J. Craig Venter Institute. Collaborators request that publications resulting from these data cite their original publication: Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type (PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30150662" target="_blank">30150662</a>).</p>
| phs001791 | dbGaP
Project description:BrainSpan Atlas of the Human Brain
| PRJNA251912 | ENA
Project description:The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity.
2021-01-15 | GSE164378 | GEO
Project description:Melanoma Brain Metastasis Atlas
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Project description:Melanoma Brain Metastasis Atlas [SlideSeq]
| PRJNA823928 | ENA
Project description:The majority of common genetic risk variants associated with neuropsychiatric disease are non-coding and are thought to exert their effects by disrupting the function of cis regulatory elements (CREs), including promoters and enhancers. Within each cell, chromatin is arranged in specific patterns to expose the repertoire of CREs required for optimal spatiotemporal regulation of gene expression. To further our understanding of the complex mechanisms that modulate transcription in the brain, we utilized frozen postmortem samples to generate the largest human brain and cell type-specific open chromatin dataset to date. Using the Assay for Transposase Accessible Chromatin followed by sequencing (ATAC-seq), we created maps of chromatin accessibility in 2 cell types (neurons and non-neurons) across 14 distinct brain regions of 5 individuals. Chromatin structure varies markedly by cell type, with neuronal chromatin displaying higher regional variability than that of non-neurons. Among our findings is an open chromatin region (OCR) specific to neurons of the striatum. When placed in the mouse, a human sequence derived from this OCR recapitulates the cell-type and regional expression pattern predicted by our ATAC-seq experiments. Furthermore, differentially accessible chromatin overlaps with the genetic architecture of neuropsychiatric traits and identifies differences in molecular pathways and biological functions. By leveraging transcription factor binding analysis, we identify protein coding and long noncoding RNAs (lncRNAs) with cell-type and brain region specificity. Our data provides a valuable resource to the research community and we provide this human brain chromatin accessibility atlas as an online database “Brain Open Chromatin Atlas (BOCA)” to facilitate interpretation.
2018-06-21 | GSE96949 | GEO