SDRS—an algorithm for analyzing large-scale dose–response data

• Published in: Bioinformatics Vol. 27; no. 20; pp. 2921 - 2923
• Main Authors: Ji, Rui-Ru, Siemers, Nathan O, Lei, Ming, Schweizer, Liang, Bruccoleri, Robert E
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.10.2011
• Subjects: Algorithms; analytical methods; Applications Note; bioinformatics; Biological and medical sciences; dose response; Dose-Response Relationship, Drug; drug therapy; drugs; Fundamental and applied biological sciences. Psychology; Gene Expression Profiling - methods; General aspects; Internet; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); microarray technology; screening; transcriptome; Transcriptome - drug effects; Algorithm; Data; Large scale
• ISSN: 1367-4803; 1367-4811; 1367-4811; 1460-2059
• DOI: 10.1093/bioinformatics/btr489

Dose–response information is critical to understanding drug effects, yet analytical methods for dose–response assays cannot cope with the dimensionality of large-scale screening data such as the microarray profiling data. To overcome this limitation, we developed and implemented the Sigmoidal Dose Response Search (SDRS) algorithm, a grid search-based method designed to handle large-scale dose–response data. This method not only calculates the pharmacological parameters for every assay, but also provides built-in statistic that enables downstream systematic analyses, such as characterizing dose response at the transcriptome level. AVAILABILITY: Bio::SDRS is freely available from CPAN (www.cpan.org). CONTACTS: ruiruji@gmail.com; bruc@acm.org Supplementary Information: Supplementary data is available at Bioinformatics online.