Title |
MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data
|
---|---|
Published in |
BMC Bioinformatics, March 2014
|
DOI | 10.1186/1471-2105-15-69 |
Pubmed ID | |
Authors |
Zhuohui Gan, Jianwu Wang, Nathan Salomonis, Jennifer C Stowe, Gabriel G Haddad, Andrew D McCulloch, Ilkay Altintas, Alexander C Zambon |
Abstract |
Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 14% |
Norway | 1 | 14% |
Mexico | 1 | 14% |
Germany | 1 | 14% |
Unknown | 3 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 4 | 57% |
Members of the public | 3 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 1 | 3% |
Singapore | 1 | 3% |
Argentina | 1 | 3% |
Brazil | 1 | 3% |
Unknown | 34 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 29% |
Researcher | 10 | 26% |
Student > Bachelor | 3 | 8% |
Professor | 3 | 8% |
Librarian | 2 | 5% |
Other | 5 | 13% |
Unknown | 4 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 12 | 32% |
Biochemistry, Genetics and Molecular Biology | 6 | 16% |
Medicine and Dentistry | 6 | 16% |
Computer Science | 5 | 13% |
Engineering | 2 | 5% |
Other | 2 | 5% |
Unknown | 5 | 13% |