Configure your dose-response analysis

Adjust the settings below to custom your analysis of dose-response analysis. Set parameters like feature sets, size filters, and transformation options to refine your results. Once configured, click "Submit" to begin.

* Required fields

Dataset summary
Name: E-TABM-585 - Nilotinib - homo_sapiens - Microarray
Doses/Concentrations: 0, 1.70e-01, 5.00e-01, 1.50e+00, 4.50e+00, 1.37e+01, 4.12e+01, 1.24e+02, 3.70e+02, 1.11e+03, 3.33e+03, 1.00e+04, 3.00e+04
Dose/Concentration units: µM
Omics type: Microarray
Feature annotation: symbols
Number of samples: 24
Species: Homo sapiens
Feature sets configuration

Select or upload gene sets to use in the dose-response analysis. Optional filtering steps remove pathways with non-informative or contradictory patterns. Clustering is automatically applied to detect substructure within gene sets.

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Gene set database: ?
Minimum set size: ?
Maximum set size: ?
Correlation Threshold: ?
Negative Correlation Threshold: ?
Data preprocessing

Preprocess dose values and choose statistical models for dose-response fitting. DoseRider applies generalized models at the pathway level using all member genes as repeated observations.

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Advanced spline parameters

These are advanced options for spline-based models. Modify only if you understand how splines are configured in dose-response modeling.

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Benchmark dose modeling

Configure parameters for Benchmark Dose (BMD) estimation using the BMDz method. The BMD is the dose at which the predicted pathway response deviates significantly from the control, defined by a configurable threshold.

Number of SD for BMD calculation: ?
Number of bootstrap iterations for BMD calculation: ?
If checked, the BMD will be calculated using the main cluster. If unchecked, the BMD will be calculated using all data points.
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Viability analysis