Dose-response modeling of high-throughput screening data - PubMed (original) (raw)
Dose-response modeling of high-throughput screening data
Fred Parham et al. J Biomol Screen. 2009 Dec.
Abstract
The National Toxicology Program is developing a high-throughput screening (HTS) program to set testing priorities for compounds of interest, to identify mechanisms of action, and potentially to develop predictive models for human toxicity. This program will generate extensive data on the activity of large numbers of chemicals in a wide variety of biochemical- and cell-based assays. The first step in relating patterns of response among batteries of HTS assays to in vivo toxicity is to distinguish between positive and negative compounds in individual assays. Here, the authors report on a statistical approach developed to identify compounds positive or negative in an HTS cytotoxicity assay based on data collected from screening 1353 compounds for concentration-response effects in 9 human and 4 rodent cell types. In this approach, the authors develop methods to normalize the data (removing bias due to the location of the compound on the 1536-well plates used in the assay) and to analyze for concentration-response relationships. Various statistical tests for identifying significant concentration-response relationships and for addressing reproducibility are developed and presented.
Figures
Figure 1
Ratio of vehicle controls to positive controls. Each point represents one row on one plate. Data from the same assay are plotted in the same color.
Figure 2
Raw data from columns 5 through 48 of the first control plate for BJ cells. Color corresponds to value of data, with blue the lowest and red the highest.
Figure 3
(A) Raw and (B) normalized data from columns 5–48 of the control plate for BJ cells. Each colored line is one column of data.
Figure 4
Raw data values from columns 5:48 of the control plates and the fitted values from the model (from equation (4)), for all plates.
Figure 5
Plot of p-value (p15) based on all concentrations, with color coding based on both p15 and p14. Results plotted are from all assays, including triplicate HepG2 assays. Red: both p15 and p14 are significant. Blue: only p15 is significant. Model response is on the normalized scale. P values less than 10−16are plotted as 10−16. Values with model response 0 (i.e. v=0) and p15=1 are omitted.
Figure 6
Normalized data values for duplicate substances on all plates used in the model, using all 15 concentration levels. X axis is the normalized data value for first occurrence of the duplicate, Y axis is the value for the second occurrence.
Figure 7
Values of the Hill parameter k by duplicate. Red: both duplicate concentration-response curves for the duplicated substance in the given assay are active. Blue: neither, or only one, is active. The vertical and horizontal lines are at the location of the two highest concentrations (0.046 and 0.092 mM). Cluster of k values along vertical or horizontal lines correspond to k values set to an arbitrary constant when v is fixed at 0 in step 7 of the algorithm; in that case, the values of k are not meaningful.
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