Title |
CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq
|
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Published in |
Genome Biology, April 2016
|
DOI | 10.1186/s13059-016-0938-8 |
Pubmed ID | |
Authors |
Tamar Hashimshony, Naftalie Senderovich, Gal Avital, Agnes Klochendler, Yaron de Leeuw, Leon Anavy, Dave Gennert, Shuqiang Li, Kenneth J. Livak, Orit Rozenblatt-Rosen, Yuval Dor, Aviv Regev, Itai Yanai |
Abstract |
Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm's C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2's increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 36% |
United Kingdom | 4 | 14% |
China | 2 | 7% |
France | 1 | 4% |
Germany | 1 | 4% |
Korea, Republic of | 1 | 4% |
Unknown | 9 | 32% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 19 | 68% |
Members of the public | 7 | 25% |
Practitioners (doctors, other healthcare professionals) | 2 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | <1% |
Sweden | 3 | <1% |
United Kingdom | 3 | <1% |
Netherlands | 2 | <1% |
Denmark | 2 | <1% |
Japan | 2 | <1% |
Australia | 1 | <1% |
South Africa | 1 | <1% |
Israel | 1 | <1% |
Other | 6 | <1% |
Unknown | 1153 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 281 | 24% |
Researcher | 205 | 17% |
Student > Master | 137 | 12% |
Student > Bachelor | 104 | 9% |
Student > Postgraduate | 53 | 4% |
Other | 140 | 12% |
Unknown | 261 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 380 | 32% |
Agricultural and Biological Sciences | 263 | 22% |
Medicine and Dentistry | 64 | 5% |
Immunology and Microbiology | 44 | 4% |
Neuroscience | 41 | 3% |
Other | 107 | 9% |
Unknown | 282 | 24% |