| Title |
Quantitative real-time RT-PCR data analysis: current concepts and the novel “gene expression’s CT difference” formula
|
|---|---|
| Published in |
Journal of Molecular Medicine, September 2006
|
| DOI | 10.1007/s00109-006-0097-6 |
| Pubmed ID | |
| Authors |
Jan H. Schefe, Kerstin E. Lehmann, Ivo R. Buschmann, Thomas Unger, Heiko Funke-Kaiser |
| Abstract |
For quantification of gene-specific mRNA, quantitative real-time RT-PCR has become one of the most frequently used methods over the last few years. This article focuses on the issue of real-time PCR data analysis and its mathematical background, offering a general concept for efficient, fast and precise data analysis superior to the commonly used comparative CT (DeltaDeltaCT) and the standard curve method, as it considers individual amplification efficiencies for every PCR. This concept is based on a novel formula for the calculation of relative gene expression ratios, termed GED (Gene Expression's CT Difference) formula. Prerequisites for this formula, such as real-time PCR kinetics, the concept of PCR efficiency and its determination, are discussed. Additionally, this article offers some technical considerations and information on statistical analysis of real-time PCR data. |
Mendeley readers
The data shown below were compiled from readership statistics for 928 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 13 | 1% |
| United Kingdom | 10 | 1% |
| Brazil | 10 | 1% |
| Canada | 6 | <1% |
| Germany | 5 | <1% |
| France | 5 | <1% |
| Spain | 4 | <1% |
| Italy | 3 | <1% |
| Argentina | 3 | <1% |
| Other | 25 | 3% |
| Unknown | 844 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 240 | 26% |
| Researcher | 180 | 19% |
| Student > Master | 132 | 14% |
| Student > Bachelor | 79 | 9% |
| Student > Doctoral Student | 61 | 7% |
| Other | 155 | 17% |
| Unknown | 81 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 484 | 52% |
| Biochemistry, Genetics and Molecular Biology | 131 | 14% |
| Medicine and Dentistry | 71 | 8% |
| Immunology and Microbiology | 20 | 2% |
| Environmental Science | 17 | 2% |
| Other | 98 | 11% |
| Unknown | 107 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 December 2023.
All research outputs
#4,696,096
of 22,786,691 outputs
Outputs from Journal of Molecular Medicine
#230
of 1,551 outputs
Outputs of similar age
#12,132
of 67,038 outputs
Outputs of similar age from Journal of Molecular Medicine
#3
of 14 outputs
Altmetric has tracked 22,786,691 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,551 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 67,038 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.