Title |
Quantitative gene profiling of long noncoding RNAs with targeted RNA sequencing
|
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Published in |
Nature Methods, March 2015
|
DOI | 10.1038/nmeth.3321 |
Pubmed ID | |
Authors |
Michael B Clark, Tim R Mercer, Giovanni Bussotti, Tommaso Leonardi, Katelin R Haynes, Joanna Crawford, Marion E Brunck, Kim-Anh Lê Cao, Gethin P Thomas, Wendy Y Chen, Ryan J Taft, Lars K Nielsen, Anton J Enright, John S Mattick, Marcel E Dinger |
Abstract |
We compared quantitative RT-PCR (qRT-PCR), RNA-seq and capture sequencing (CaptureSeq) in terms of their ability to assemble and quantify long noncoding RNAs and novel coding exons across 20 human tissues. CaptureSeq was superior for the detection and quantification of genes with low expression, showed little technical variation and accurately measured differential expression. This approach expands and refines previous annotations and simultaneously generates an expression atlas. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 5 | 16% |
Australia | 3 | 10% |
Germany | 2 | 6% |
Switzerland | 2 | 6% |
France | 2 | 6% |
United Kingdom | 2 | 6% |
China | 1 | 3% |
Spain | 1 | 3% |
Netherlands | 1 | 3% |
Other | 1 | 3% |
Unknown | 11 | 35% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 18 | 58% |
Members of the public | 11 | 35% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 2% |
Germany | 2 | <1% |
Finland | 2 | <1% |
United Kingdom | 2 | <1% |
Italy | 1 | <1% |
Sweden | 1 | <1% |
Korea, Republic of | 1 | <1% |
Czechia | 1 | <1% |
Belgium | 1 | <1% |
Other | 5 | 1% |
Unknown | 318 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 90 | 26% |
Student > Ph. D. Student | 84 | 25% |
Student > Master | 35 | 10% |
Professor > Associate Professor | 18 | 5% |
Professor | 17 | 5% |
Other | 57 | 17% |
Unknown | 39 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 151 | 44% |
Biochemistry, Genetics and Molecular Biology | 97 | 29% |
Medicine and Dentistry | 13 | 4% |
Neuroscience | 7 | 2% |
Computer Science | 6 | 2% |
Other | 23 | 7% |
Unknown | 43 | 13% |