Results 11 to 20 of about 3,543,075 (195)

Single-nucleus and single-cell transcriptomes compared in matched cortical cell types.

PLoS ONE, 2018
Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based
Trygve E Bakken, Rebecca D Hodge, Jeremy A Miller, Zizhen Yao, Thuc Nghi Nguyen, Brian Aevermann, Eliza Barkan, Darren Bertagnolli, Tamara Casper, Nick Dee, Emma Garren, Jeff Goldy, Lucas T Graybuck, Matthew Kroll, Roger S Lasken, Kanan Lathia, Sheana Parry, Christine Rimorin, Richard H Scheuermann, Nicholas J Schork, Soraya I Shehata, Michael Tieu, John W Phillips, Amy Bernard, Kimberly A Smith, Hongkui Zeng, Ed S Lein, Bosiljka Tasic   +27 more
doaj   +4 more sources

High-Throughput Single-Cell Transcriptome Profiling of Plant Cell Types [PDF]

Cell Reports, 2019
Summary: Single-cell transcriptome profiling of heterogeneous tissues can provide high-resolution windows into developmental dynamics and environmental responses, but its application to plants has been limited.
Christine N. Shulse, Benjamin J. Cole, Doina Ciobanu, Junyan Lin, Yuko Yoshinaga, Mona Gouran, Gina M. Turco, Yiwen Zhu, Ronan C. O’Malley, Siobhan M. Brady, Diane E. Dickel   +10 more
doaj   +5 more sources

Identifying cell types from spatially referenced single-cell expression datasets.

PLoS Computational Biology, 2014
Complex tissues, such as the brain, are composed of multiple different cell types, each of which have distinct and important roles, for example in neural function.
Jean-Baptiste Pettit, Raju Tomer, Kaia Achim, Sylvia Richardson, Lamiae Azizi, John Marioni   +5 more
doaj   +4 more sources

Cell type identification from single-cell transcriptomes in melanoma [PDF]

BMC Medical Genomics, 2021
Background Single-cell sequencing approaches allow gene expression to be measured at the single-cell level, providing opportunities and challenges to study the aetiology of complex diseases, including cancer.
Qiuyan Huo, Yu Yin, Fangfang Liu, Yuying Ma, Liming Wang, Guimin Qin   +5 more
doaj   +3 more sources

Toward Plant Single Cell Type Systems Biology [PDF]

Frontiers in Plant Science, 2016
The molecular responses of a plant to a stress and the molecular profiles of plant organs during their development and differentiation are the reflection of the contribution from different cell types composing the plant and the organs. Hence, a major limitation to understanding plant cellular and molecular responses in different cells is the ...
Marc eLibault, Sixue eChen
doaj   +3 more sources

Neuronal cell types in the fly: single-cell anatomy meets single-cell genomics [PDF]

Current Opinion in Neurobiology, 2019
At around 150 000 neurons, the adult Drosophila melanogaster central nervous system is one of the largest species, for which a complete cellular catalogue is imminent. While numerically much simpler than mammalian brains, its complexity is still difficult to parse without grouping neurons into consistent types, which can number 1-1000 cells per ...
Bates, Alexander Shakeel, Janssens, Jasper, Jefferis, Gregory SXE, Aerts, Stein   +3 more
openaire   +4 more sources

Evolutionary cell type mapping with single-cell genomics

Trends in Genetics, 2021
A fundamental characteristic of animal multicellularity is the spatial coexistence of functionally specialized cell types that are all encoded by a single genome sequence. Cell type transcriptional programs are deployed and maintained by regulatory mechanisms that control the asymmetric, differential access to genomic information in each cell.
Tanay, Amos, Sebé-Pedrós, Arnau
openaire   +2 more sources

Cell type prioritization in single-cell data [PDF]

Nature Biotechnology, 2019
We present a machine-learning method to prioritize the cell types most responsive to biological perturbations within high-dimensional single-cell data. We validate our method, Augur (https://github.com/neurorestore/Augur), on a compendium of single-cell RNA-seq, chromatin accessibility, and imaging transcriptomics datasets. We apply Augur to expose the
Michael A. Skinnider, Jordan W. Squair, Claudia Kathe, Mark A. Anderson, Matthieu Gautier, Kaya J.E. Matson, Marco Milano, Thomas H. Hutson, Quentin Barraud, Aaron A. Phillips, Leonard J. Foster, Gioele La Manno, Ariel J. Levine, Grégoire Courtine   +13 more
openaire   +3 more sources

Single cell RNA-sequencing: replicability of cell types [PDF]

Current Opinion in Neurobiology, 2019
Recent technical advances have enabled transcriptomics experiments at an unprecedented scale, and single-cell profiles from neural tissue are accumulating rapidly. There has been considerable effort to use these profiles to understand cell diversity, primarily through unsupervised clustering and differential expression analysis.
Megan Crow, Jesse Gillis
openaire   +2 more sources

Cell Type Purification by Single-Cell Transcriptome-Trained Sorting [PDF]

SSRN Electronic Journal, 2018
Traditional cell type enrichment using fluorescence activated cell sorting (FACS) relies on methods that specifically label the cell type of interest. Here we propose GateID, a computational method that combines single-cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice.
Baron, C.S., Barve, A., Muraro, M.J., Linden, R. van der, Dharmadhikari, G., Lyubimova, A., Koning, E.J.P. de, Oudenaarden, A. van   +7 more
openaire   +5 more sources