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

Integrated analysis of multimodal single-cell data

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

Integrated analysis of multimodal single-cell data

Project description:Integrated analysis of multimodal single-cell data

| PRJNA690251 | ENA

Melanoma Brain Metastasis Atlas

Project description:Melanoma Brain Metastasis Atlas

| PRJNA768859 | ENA

BrainSpan Atlas of the Human Brain

Project description:BrainSpan Atlas of the Human Brain

| PRJNA251912 | ENA

Melanoma Brain Metastasis Atlas [SlideSeq]

Project description:Melanoma Brain Metastasis Atlas [SlideSeq]