Robust dose-response curve estimation applied to high content screening data analysis.
Source Code Biol Med
; 9(1): 27, 2014.
Article
en En
| MEDLINE
| ID: mdl-25614758
ABSTRACT
BACKGROUND AND METHOD:
Successfully automated sigmoidal curve fitting is highly challenging when applied to large data sets. In this paper, we describe a robust algorithm for fitting sigmoid dose-response curves by estimating four parameters (floor, window, shift, and slope), together with the detection of outliers. We propose two improvements over current methods for curve fitting. The first one is the detection of outliers which is performed during the initialization step with correspondent adjustments of the derivative and error estimation functions. The second aspect is the enhancement of the weighting quality of data points using mean calculation in Tukey's biweight function. RESULTS ANDCONCLUSION:
Automatic curve fitting of 19,236 dose-response experiments shows that our proposed method outperforms the current fitting methods provided by MATLAB®;'s nlinfit function and GraphPad's Prism software.
Texto completo:
1
Bases de datos:
MEDLINE
Tipo de estudio:
Diagnostic_studies
/
Screening_studies
Idioma:
En
Revista:
Source Code Biol Med
Año:
2014
Tipo del documento:
Article
País de afiliación:
Estados Unidos