Abstract
BackgroundOur SigWin-detector discovers significantly enriched windows of (genomic) elements in any sequence of values (genes or other genomic elements in a DNA sequence) in a fast and reproducible way. However, since it is grid based, only (life) scientists with access to the grid can use this tool. Therefore and on request, we have developed the SigWinR package which makes the SigWin-detector available to a much wider audience. At the same time, we have introduced several improvements to its algorithm as well as its functionality, based on the feedback of SigWin-detector end users.FindingsTo allow usage of the SigWin-detector on a desktop computer, we have rewritten it as a package for R: SigWinR. R is a free and widely used multi platform software environment for statistical computing and graphics. The package can be installed and used on all platforms for which R is available. The improvements involve: a visualization of the input-sequence values supporting the interpretation of Ridgeograms; a visualization allowing for an easy interpretation of enriched or depleted regions in the sequence using windows of pre-defined size; an option that allows the analysis of circular sequences, which results in rectangular Ridgeograms; an application to identify regions of co-altered gene expression (ROCAGEs) with a real-life biological use-case; adaptation of the algorithm to allow analysis of non-regularly sampled data using a constant window size in physical space without resampling the data. To achieve this, support for analysis of windows with an even number of elements was added.ConclusionBy porting the SigWin-detector as an R package, SigWinR, improving its algorithm and functionality combined with adequate performance, we have made SigWin-detector more useful as well as more easily accessible to scientists without a grid infrastructure.
Highlights
For the detection of significantly enriched windows of elements in any sequence of values in a fast and reproducible way, we developed and published a workflow and gridbased tool; SigWin-detector[1]
By porting the SigWin-detector as an R package, SigWinR, improving its algorithm and functionality combined with adequate performance, we have made SigWin-detector more useful as well as more accessible to scientists without a grid infrastructure
The development of SigWindetector was originally motivated by the need to identify regions of increased gene expression (RIDGEs) in the human transcriptome map (HTM) [1,2], see Additional file 1
Summary
For the detection of significantly enriched windows of elements in any sequence of values in a fast and reproducible way, we developed and published a workflow and gridbased tool; SigWin-detector[1]. SigWin-detector visualizes significantly enriched windows by Ridgeograms; the sequence is (page number not for citation purposes) Visualizing input-sequence values Ridgeograms are the standard output of SigWinR.
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