Title |
Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes
|
---|---|
Published in |
Genome Biology, June 2002
|
DOI | 10.1186/gb-2002-3-7-research0034 |
Pubmed ID | |
Authors |
Jo Vandesompele, Katleen De Preter, Filip Pattyn, Bruce Poppe, Nadine Van Roy, Anne De Paepe, Frank Speleman |
Abstract |
Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 25% |
United Kingdom | 4 | 20% |
Canada | 2 | 10% |
India | 1 | 5% |
Switzerland | 1 | 5% |
Japan | 1 | 5% |
Spain | 1 | 5% |
Unknown | 5 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 11 | 55% |
Scientists | 8 | 40% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 87 | 1% |
Brazil | 55 | <1% |
United Kingdom | 54 | <1% |
Germany | 47 | <1% |
Belgium | 26 | <1% |
Spain | 22 | <1% |
Mexico | 21 | <1% |
France | 20 | <1% |
Portugal | 19 | <1% |
Other | 222 | 3% |
Unknown | 7777 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 2105 | 25% |
Researcher | 1706 | 20% |
Student > Master | 1134 | 14% |
Student > Bachelor | 709 | 8% |
Student > Doctoral Student | 519 | 6% |
Other | 1151 | 14% |
Unknown | 1026 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 3904 | 47% |
Biochemistry, Genetics and Molecular Biology | 1439 | 17% |
Medicine and Dentistry | 641 | 8% |
Neuroscience | 175 | 2% |
Immunology and Microbiology | 163 | 2% |
Other | 757 | 9% |
Unknown | 1271 | 15% |