Abstract
BackgroundThe exploration of microarray data and data from other high-throughput projects for hypothesis generation has become a vital aspect of post-genomic research. For the non-bioinformatics specialist, however, many of the currently available tools provide overwhelming amounts of data that are presented in a non-intuitive way.Methodology/Principal FindingsIn order to facilitate the interpretation and analysis of microarray data and data from other large-scale data sets, we have developed a tool, which we have dubbed the electronic Fluorescent Pictograph – or eFP – Browser, available at http://www.bar.utoronto.ca/, for exploring microarray and other data for hypothesis generation. This eFP Browser engine paints data from large-scale data sets onto pictographic representations of the experimental samples used to generate the data sets. We give examples of using the tool to present Arabidopsis gene expression data from the AtGenExpress Consortium (Arabidopsis eFP Browser), data for subcellular localization of Arabidopsis proteins (Cell eFP Browser), and mouse tissue atlas microarray data (Mouse eFP Browser).Conclusions/SignificanceThe eFP Browser software is easily adaptable to microarray or other large-scale data sets from any organism and thus should prove useful to a wide community for visualizing and interpreting these data sets for hypothesis generation.
Highlights
With the prevalence of large-scale data sets as a resource for biological research, tools for collecting and examining microarray and other high-throughput results are becoming increasingly significant
The electronic Fluorescent Pictograph (eFP) Browser is implemented in Python and makes use of the Python Imaging Library (PIL) Build 1.1.5, which we modified to provide an optimized flood pixel replacement function called replaceFill, and other Python modules, as described on the eFP Browser development homepage
We hope that many researchers will be able to use the electronic Fluorescent Pictograph (eFP) Browser both to understand particular microarray or other experimental results, as well as to communicate their own findings
Summary
With the prevalence of large-scale data sets as a resource for biological research, tools for collecting and examining microarray and other high-throughput results are becoming increasingly significant. The electronic Fluorescent Pictograph (eFP) Browser was developed to aid in further interpretation of gene expression data and data from other large-scale data sets. In order to facilitate the interpretation and analysis of microarray data and data from other large-scale data sets, we have developed a tool, which we have dubbed the electronic Fluorescent Pictograph – or eFP – Browser, available at http:// www.bar.utoronto.ca/, for exploring microarray and other data for hypothesis generation. This eFP Browser engine paints data from large-scale data sets onto pictographic representations of the experimental samples used to generate the data sets. The eFP Browser software is adaptable to microarray or other largescale data sets from any organism and should prove useful to a wide community for visualizing and interpreting these data sets for hypothesis generation
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