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Mendeley readers
Chapter title |
Study Design for Sequencing Studies
|
---|---|
Chapter number | 3 |
Book title |
Statistical Genomics
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3578-9_3 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3576-5, 978-1-4939-3578-9
|
Authors |
Loren A. Honaas, Naomi S. Altman, Martin Krzywinski, Honaas, Loren A., Altman, Naomi S., Krzywinski, Martin |
Editors |
Ewy Mathé, Sean Davis |
Abstract |
Once a biochemical method has been devised to sample RNA or DNA of interest, sequencing can be used to identify the sampled molecules with high fidelity and low bias. High-throughput sequencing has therefore become the primary data acquisition method for many genomics studies and is being used more and more to address molecular biology questions. By applying principles of statistical experimental design, sequencing experiments can be made more sensitive to the effects under study as well as more biologically sound, hence more replicable. |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 1 | 4% |
Unknown | 23 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 33% |
Researcher | 4 | 17% |
Professor > Associate Professor | 2 | 8% |
Lecturer | 1 | 4% |
Professor | 1 | 4% |
Other | 3 | 13% |
Unknown | 5 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 8 | 33% |
Biochemistry, Genetics and Molecular Biology | 6 | 25% |
Neuroscience | 2 | 8% |
Computer Science | 1 | 4% |
Unknown | 7 | 29% |