Dear Group Members,
I would like to know your opinion and views on "plotting high dimensional data" where you exceeds the data range of MS Excel. You can share your views on techniques, tools (Matlab, R, gnuplot, XMGRACE etc), types of plots for better understanding and resolution. This is not a limited area, you can expand it to any direction depending on the need.
I would like to request you to participate on this topic, please provide your views on choosing the best tool.
Best Regards,
Amit Kumar Banerjee
Hello.
I do follow some of your activities.
I work with microarray data exploratory analysis. So Excel is the worst solution to handle all of the tables, it can be applied only on later stages when you reduce your data dimension. For me the best for the moment is R.
Besides, it should be mentioned the need of data transformation techniques and selection procedures, because I think in most of cases there is no need to show all the data in one representation. when you describe your data you can choose a way show them in another way, as a histogram or distribution, or Vienn diagram etc.
Regards
Alex
Dear Alex, You are absolutely right, I do feel same, please let me know how is R package's performance with comparison to Matlab and Scilab in handling microarray high dimension data, will be waiting for your interesting answer.
Dear Amit,
I use basically R for this purpose, as it is more useful to extract also annotations from Bioconductor and give more senses to the graphics. But, its basic disadvantage, especially for the novice, is lack of graphical interface.
So I would advice for students to use primary a software with the interface to understand very well the way to make graphics, formulas and parameters necessary to make the picture, and than train in R doing the same things.
Still, I think R is much better for this task and much faster for a Windows environment.
I am interested in this topic too...can Scilab handle the microarray data analysis, with its high dimensional data plotting? Considering Scilab can handle Parallel Computing.
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