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Dose Response Analysis Pipeline (DRAP)

Web-based application for high-throughput dose response analysis

Benefits and Features

  • Use nonlinear equations to represent complicated biological relationships.
  • Fit your experimental data to curves and get IC50 and IC90 using a single application.
  • Use DRAP with cell-based assay data, growth measurements, ELISA data, and more.
  • Simplify analysis for large amounts of 96-well data.
  • Analyze unlimited numbers of plates automatically without the need to cut and paste between statistics programs.
  • Graphically design your experimental plate layouts using an intuitive 96-well plate interface.

Access the software.

Overview

Many researchers conduct dose response assays in 96-well plates, but managing and analyzing data from multiple plates can be laborious. To enable the high throughput analysis of dose response assays, we have developed a Web-based software called Dose Response Analysis Pipeline (DRAP). DRAP uses an automated workflow to read dosage plate layout files and experimental data from plate readers; construct non-linear dose-response curves; determine inhibitory concentrations (IC50 and IC90) for each treatment; and generate analysis reports with publication-quality images. DRAP includes modules for the visual design of dosage files using plate layouts and for the management of an unlimited number of 96-well dosage and response files.

Access

This software is provided free of charge by the National Institute of Allergy and Infectious Diseases.

Background

DRAP was developed by the NIAID Office of Cyber Infrastructure and Computational Biology Bioinformatics and Computational Biosciences Branch (OCICB/BCBB) in collaboration with the NIAID Laboratory of Malaria and Vector Research (LMVR).

The Web interface of DRAP was developed using the latest Google Web Toolkit framework, while all server-side calculations and optimizations were performed using the open source R statistics package. The software has already saved significant time and effort for LMVR researchers who previously used Excel and Prism.

Last Updated March 20, 2012

Last Reviewed June 17, 2010