Title |
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
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Published in |
Genome Medicine, August 2017
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DOI | 10.1186/s13073-017-0467-4 |
Pubmed ID | |
Authors |
Ashraful Haque, Jessica Engel, Sarah A. Teichmann, Tapio Lönnberg |
Abstract |
RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 44 | 28% |
United Kingdom | 20 | 13% |
Australia | 12 | 8% |
France | 6 | 4% |
Canada | 4 | 3% |
Spain | 4 | 3% |
Sweden | 3 | 2% |
Netherlands | 2 | 1% |
Italy | 2 | 1% |
Other | 10 | 6% |
Unknown | 49 | 31% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 78 | 50% |
Members of the public | 74 | 47% |
Science communicators (journalists, bloggers, editors) | 4 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 3110 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 619 | 20% |
Researcher | 472 | 15% |
Student > Bachelor | 358 | 12% |
Student > Master | 322 | 10% |
Student > Doctoral Student | 152 | 5% |
Other | 310 | 10% |
Unknown | 877 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 832 | 27% |
Agricultural and Biological Sciences | 389 | 13% |
Medicine and Dentistry | 209 | 7% |
Neuroscience | 180 | 6% |
Immunology and Microbiology | 166 | 5% |
Other | 380 | 12% |
Unknown | 954 | 31% |