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A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments

Overview of attention for article published in BMC Bioinformatics, December 2017
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  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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6 X users

Citations

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Title
A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments
Published in
BMC Bioinformatics, December 2017
DOI 10.1186/s12859-017-1949-5
Pubmed ID
Authors

Michael T. Ganger, Geoffrey D. Dietz, Sarah J. Ewing

Abstract

qPCR has established itself as the technique of choice for the quantification of gene expression. Procedures for conducting qPCR have received significant attention; however, more rigorous approaches to the statistical analysis of qPCR data are needed. Here we develop a mathematical model, termed the Common Base Method, for analysis of qPCR data based on threshold cycle values (C q ) and efficiencies of reactions (E). The Common Base Method keeps all calculations in the logscale as long as possible by working with log10(E) ∙ C q , which we call the efficiency-weighted C q value; subsequent statistical analyses are then applied in the logscale. We show how efficiency-weighted C q values may be analyzed using a simple paired or unpaired experimental design and develop blocking methods to help reduce unexplained variation. The Common Base Method has several advantages. It allows for the incorporation of well-specific efficiencies and multiple reference genes. The method does not necessitate the pairing of samples that must be performed using traditional analysis methods in order to calculate relative expression ratios. Our method is also simple enough to be implemented in any spreadsheet or statistical software without additional scripts or proprietary components.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 232 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 22%
Student > Bachelor 34 15%
Student > Master 28 12%
Researcher 26 11%
Student > Doctoral Student 12 5%
Other 27 12%
Unknown 54 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 64 28%
Agricultural and Biological Sciences 54 23%
Medicine and Dentistry 9 4%
Immunology and Microbiology 7 3%
Pharmacology, Toxicology and Pharmaceutical Science 5 2%
Other 31 13%
Unknown 62 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 20 June 2020.
All research outputs
#7,763,985
of 25,074,338 outputs
Outputs from BMC Bioinformatics
#2,837
of 7,643 outputs
Outputs of similar age
#142,465
of 450,037 outputs
Outputs of similar age from BMC Bioinformatics
#46
of 132 outputs
Altmetric has tracked 25,074,338 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,643 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 62% 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 450,037 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 68% of its contemporaries.
We're also able to compare this research output to 132 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 65% of its contemporaries.