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SAFA: Semi-automated footprinting analysis software for high-throughput quantification of nucleic acid footprinting experiments
Author(s) -
Rhiju Das,
Alain Laederach,
Samuel M. Pearlman,
Daniel Herschlag,
Russ B. Altman
Publication year - 2005
Publication title -
rna
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.037
H-Index - 171
eISSN - 1469-9001
pISSN - 1355-8382
DOI - 10.1261/rna.7214405
Subject(s) - footprinting , biology , software , dna footprinting , computational biology , biological system , computer science , biochemistry , dna binding protein , dna , gene , base sequence , transcription factor , programming language
Footprinting is a powerful and widely used tool for characterizing the structure, thermodynamics, and kinetics of nucleic acid folding and ligand binding reactions. However, quantitative analysis of the gel images produced by footprinting experiments is tedious and time-consuming, due to the absence of informatics tools specifically designed for footprinting analysis. We have developed SAFA, a semi-automated footprinting analysis software package that achieves accurate gel quantification while reducing the time to analyze a gel from several hours to 15 min or less. The increase in analysis speed is achieved through a graphical user interface that implements a novel methodology for lane and band assignment, called "gel rectification," and an optimized band deconvolution algorithm. The SAFA software yields results that are consistent with published methodologies and reduces the investigator-dependent variability compared to less automated methods. These software developments simplify the analysis procedure for a footprinting gel and can therefore facilitate the use of quantitative footprinting techniques in nucleic acid laboratories that otherwise might not have considered their use. Further, the increased throughput provided by SAFA may allow a more comprehensive understanding of molecular interactions. The software and documentation are freely available for download at http://safa.stanford.edu.

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