| Title |
BeadArray Expression Analysis Using Bioconductor
|
|---|---|
| Published in |
PLoS Computational Biology, December 2011
|
| DOI | 10.1371/journal.pcbi.1002276 |
| Pubmed ID | |
| Authors |
Matthew E. Ritchie, Mark J. Dunning, Mike L. Smith, Wei Shi, Andy G. Lynch |
| Abstract |
Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 234 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 4% |
| United Kingdom | 7 | 3% |
| Italy | 4 | 2% |
| Germany | 3 | 1% |
| Netherlands | 3 | 1% |
| Ukraine | 2 | <1% |
| Sweden | 2 | <1% |
| France | 2 | <1% |
| Spain | 2 | <1% |
| Other | 9 | 4% |
| Unknown | 191 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 72 | 31% |
| Student > Ph. D. Student | 57 | 24% |
| Student > Master | 25 | 11% |
| Professor > Associate Professor | 16 | 7% |
| Student > Bachelor | 13 | 6% |
| Other | 33 | 14% |
| Unknown | 18 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 115 | 49% |
| Biochemistry, Genetics and Molecular Biology | 33 | 14% |
| Medicine and Dentistry | 20 | 9% |
| Computer Science | 13 | 6% |
| Mathematics | 11 | 5% |
| Other | 22 | 9% |
| Unknown | 20 | 9% |