Impact of Smoothing on Parameter Estimation in Quantitative DNA Amplification Experiments | Zendy

AndrejNikolai Spiess | Zendy; Claudia Deutschmann | Zendy; Michał Burdukiewicz | Zendy; Ralf Himmelreich | Zendy; Katharina Klat | Zendy; Peter Schierack | Zendy; Stefan Rödiger | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Impact of Smoothing on Parameter Estimation in Quantitative DNA Amplification Experiments

Author(s) -

AndrejNikolai Spiess,

Claudia Deutschmann,

Michał Burdukiewicz,

Ralf Himmelreich,

Katharina Klat,

Peter Schierack,

Stefan Rödiger

Publication year - 2014

Publication title -

clinical chemistry

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.705

H-Index - 218

eISSN - 1530-8561

pISSN - 0009-9147

DOI - 10.1373/clinchem.2014.230656

Subject(s) - smoothing , replicate , computer science , digital polymerase chain reaction , algorithm , sensitivity (control systems) , preprocessor , filter (signal processing) , selection (genetic algorithm) , noise (video) , statistics , data mining , mathematics , artificial intelligence , biology , polymerase chain reaction , engineering , genetics , electronic engineering , image (mathematics) , computer vision , gene

Quantification cycle (Cq) and amplification efficiency (AE) are parameters mathematically extracted from raw data to characterize quantitative PCR (qPCR) reactions and quantify the copy number in a sample. Little attention has been paid to the effects of preprocessing and the use of smoothing or filtering approaches to compensate for noisy data. Existing algorithms largely are taken for granted, and it is unclear which of the various methods is most informative. We investigated the effect of smoothing and filtering algorithms on amplification curve data.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research