ArticleCell2019
Cell Type Purification by Single-Cell Transcriptome-Trained Sorting.
Article in Cell, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
37 citing papers in PubMed, 68 citations in OpenAlex.
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- Novel microglial transcriptional signatures promote social and cognitive deficits following repeated social defeat.Communications biology · 2024Article
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- Regulation of blood-brain barrier integrity byScience advances · 2024Article
- Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets.Genome biology · 2023Review
- Fishing Innate Immune System Properties through the Transcriptomic Single-Cell Data ofBiology · 2023Review
- Cell Granularity Reflects Immune Cell Function and Enables Selection of Lymphocytes with Superior Attributes for Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Microenvironmental control of hematopoietic stem cell fate via CXCL8 and protein kinase C.Cell reports · 2023Article
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- sortChIC enables detailed chromatin analysis of rare cell types.Nature genetics · 2023Article
- Elucidating the neuroimmunology of traumatic brain injury: methodological approaches to unravel intercellular communication and function.Frontiers in cellular neuroscience · 2023Review
- Tissue specific imprinting on innate lymphoid cells during homeostasis and disease process revealed by integrative inference of single-cell transcriptomics.Frontiers in immunology · 2023Article
- Droplets microfluidics platform-A tool for single cell research.Frontiers in bioengineering and biotechnology · 2023Review
- Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Single-Cell Sequencing in Rheumatic Diseases: New Insights from the Perspective of the Cell Type.Aging and disease · 2022Article
- Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta.Arteriosclerosis, thrombosis, and vascular biology · 2022Article
- Single-cell analyses reveal early thymic progenitors and pre-B cells in zebrafish.The Journal of experimental medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Much of current molecular and cell biology research relies on the ability to purify cell types by fluorescence-activated cell sorting (FACS). FACS typically relies on the ability to label cell types of interest with antibodies or fluorescent transgenic constructs. However, antibody availability is often limited, and genetic manipulation is labor intensive or impossible in the case of primary human tissue. To date, no systematic method exists to enrich for cell types without a priori knowledge of cell-type markers. Here, we propose GateID, a computational method that combines single-cell transcriptomics with FACS index sorting to purify cell types of choice using only native cellular properties such as cell size, granularity, and mitochondrial content. We validate GateID by purifying various cell types from zebrafish kidney marrow and the human pancreas to high purity without resorting to specific antibodies or transgenes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.