Balony: a software package for analysis of data generated by synthetic genetic array experiments

BackgroundSynthetic Genetic Array (SGA) analysis is a procedure which has been developed to allow the systematic examination of large numbers of double mutants in the yeast Saccharomyces cerevisiae. The aim of these experiments is to identify genetic interactions between pairs of genes. These experiments generate a number of images of ordered arrays of yeast colonies which must be analyzed in order to quantify the extent of the genetic interactions. We have designed software that is able to analyze virtually any image of regularly arrayed colonies and allows the user significant flexibility over the analysis procedure.Results“Balony” is freely available software which enables the extraction of quantitative data from array-based genetic screens. The program follows a multi-step process, beginning with the optional preparation of plate images from single or composite images. Next, the colonies are identified on a plate and the pixel area of each is measured. This is followed by a scoring module which normalizes data and pairs control and experimental data files. The final step is analysis of the scored data, where the strength and reproducibility of genetic interactions can be visualized and cross-referenced with information on each gene to provide biological insights into the results of the screen.ConclusionsAnalysis of SGA screens with Balony can be either automated or highly interactive, enabling the user to customize the process to their specific needs. Quantitative data can be extracted at each stage for external analysis if required. Beyond SGA, this software can be used for analyzing many types of plate-based high-throughput screens.

[1]  A. Tong,et al.  Synthetic genetic array analysis in Saccharomyces cerevisiae. , 2006, Methods in molecular biology.

[2]  Gary D Bader,et al.  The Genetic Landscape of a Cell , 2010, Science.

[3]  Pierre Baldi,et al.  A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes , 2001, Bioinform..

[4]  Leopold Parts,et al.  SGAtools: one-stop analysis and visualization of array-based genetic interaction screens , 2013, Nucleic Acids Res..

[5]  H. Bussey,et al.  Exploring genetic interactions and networks with yeast , 2007, Nature Reviews Genetics.

[6]  Sean R. Collins,et al.  A strategy for extracting and analyzing large-scale quantitative epistatic interaction data , 2006, Genome Biology.

[7]  Mike Tyers,et al.  High-resolution genetic mapping with ordered arrays of Saccharomyces cerevisiae deletion mutants. , 2002, Genetics.

[8]  W. Raub.  From the National Institutes of Health. , 1990, JAMA.

[9]  John C. Dittmar,et al.  ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data , 2010, BMC Bioinformatics.

[10]  Gary D Bader,et al.  Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants , 2001, Science.

[11]  David Botstein,et al.  SGD: Saccharomyces Genome Database , 1998, Nucleic Acids Res..

[12]  Gary D Bader,et al.  Quantitative analysis of fitness and genetic interactions in yeast on a genome scale , 2010, Nature Methods.

[13]  W. Cleveland.  Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .

[14]  Ws. Rasband.  ImageJ, U.S. National Institutes of Health, Bethesda, Maryland, USA , 2011 .