DataPflex: a MATLAB-based tool for the manipulation and visualization of multidimensional datasets

DataPflex: a MATLAB-based tool for the manipulation and visualization of multidimensional datasets
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DOI:
10.1093/bioinformatics/btp667
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发表时间:
2010-02-01
期刊:
影响因子:
5.8
通讯作者:
Espelin, Christopher W.
Espelin, Christopher W.
中科院分区:
生物学3区
文献类型:
--
作者:
Hendriks, Bart S.;Espelin, Christopher W.

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动机:DataPfex是一款基于MATLAB的应用程序,可简化多维数据集的操作和可视化。DataPflex的优势在于直观的图形用户界面,可以高效地合并、操作和可视化由多路蛋白质测量平台生成的高维数据,这些平台包括但不限于Luminex或Meso-Scale Discovery。这种数据通常可以以多维数据集的形式表示[例如(时间x刺激x抑制剂x抑制剂浓度x细胞类型x测量)]。对于在多个维度上以组合方式进行测量的情况,需要一种工具来有效地操作和重组这些数据以实现可视化。DataPflex除了接受测量维度之外,还接受最多包含五个任意维度的数据。数据从简单的。Xls格式,并可以导出为matlab或。Xls.数据维度可以以折线图、条形图、曲面图、热图、IC50‘S等自定义绘图集合的形式进行重新排序、细分、合并、归一化和可视化。利用MATLAB中的开源实现,可以轻松扩展自定义绘图例程,并与更复杂的分析工具集成。
Motivation: DataPfex is aMATLAB-based application that facilitates the manipulation and visualization of multidimensional datasets. The strength of DataPflex lies in the intuitive graphical user interface for the efficient incorporation, manipulation and visualization of high-dimensional data that can be generated by multiplexed protein measurement platforms including, but not limited to Luminex or Meso-Scale Discovery. Such data can generally be represented in the form of multidimensional datasets [for example ( time x stimulation x inhibitor x inhibitor concentration x cell type x measurement)]. For cases where measurements are made in a combinational fashion across multiple dimensions, there is a need for a tool to efficiently manipulate and reorganize such data for visualization. DataPflex accepts data consisting of up to five arbitrary dimensions in addition to a measurement dimension. Data are imported from a simple. xls format and can be exported to MATLAB or. xls. Data dimensions can be reordered, subdivided, merged, normalized and visualized in the form of collections of line graphs, bar graphs, surface plots, heatmaps, IC50's and other custom plots. Open source implementation in MATLAB enables easy extension for custom plotting routines and integration with more sophisticated analysis tools.