Journal ArticleDOI
Analyzing real-time PCR data by the comparative C(T) method.
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TLDR
This protocol provides an overview of the comparative CT method for quantitative gene expression studies and various examples to present quantitative gene Expression data using this method.Abstract:
Two different methods of presenting quantitative gene expression exist: absolute and relative quantification. Absolute quantification calculates the copy number of the gene usually by relating the PCR signal to a standard curve. Relative gene expression presents the data of the gene of interest relative to some calibrator or internal control gene. A widely used method to present relative gene expression is the comparative C(T) method also referred to as the 2 (-DeltaDeltaC(T)) method. This protocol provides an overview of the comparative C(T) method for quantitative gene expression studies. Also presented here are various examples to present quantitative gene expression data using this method.read more
Citations
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Ascophyllum nodosum extract biostimulants and their role in enhancing tolerance to drought stress in tomato plants.
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References
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Journal ArticleDOI
Analysis of relative gene expression data using real-time quantitative pcr and the 2(-delta delta c(t)) method
TL;DR: The 2-Delta Delta C(T) method as mentioned in this paper was proposed to analyze the relative changes in gene expression from real-time quantitative PCR experiments, and it has been shown to be useful in the analysis of realtime, quantitative PCR data.
Journal ArticleDOI
A new mathematical model for relative quantification in real-time RT-PCR.
TL;DR: This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript and presents a new mathematical model that needs no calibration curve.
Journal ArticleDOI
Cluster analysis and display of genome-wide expression patterns
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Journal ArticleDOI
A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer
Soonmyung Paik,Steven Shak,Gong Tang,Chungyeul Kim,Joffre B. Baker,Maureen T. Cronin,Frederick L. Baehner,Michael G. Walker,Drew Watson,Taesung Park,William Hiller,Edwin R. Fisher,D. Lawrence Wickerham,John Bryant,Norman Wolmark +14 more
TL;DR: The recurrence score has been validated as quantifying the likelihood of distant recurrence in tamoxifen-treated patients with node-negative, estrogen-receptor-positive breast cancer and could be used as a continuous function to predict distant recurrent in individual patients.
Journal ArticleDOI
Real-time quantification of microRNAs by stem–loop RT–PCR
Caifu Chen,Dana Ridzon,Adam Broomer,Zhaohui Zhou,Danny H. Lee,Julie T. Nguyen,Maura Barbisin,Nan Lan Xu,Vikram R. Mahuvakar,Mark R. Andersen,Kaiqin Lao,Kenneth J. Livak,Karl J. Guegler +12 more
TL;DR: A novel microRNA quantification method has been developed using stem–loop RT followed by TaqMan PCR analysis, which enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases.