E-learning in analysis of genomic and proteomic data 3. Software

Nowadays, there exists a lot of software (SW) solutions for a data analyst in biomedicine. These solutions range from basic and flexible script all yourself environments (R, Matlab, Maple) to more sophisticated, but not flexible click and go SW tools (e.g. STATISTICA, SPSS). The former ask for a bit of programming on command line basis, the latter just a basic knowledge of placing cursor and double clicking (both of course the knowledge of the statistical methods used). As each of these approaches has its advantages over the other one, there are tendences, mostly for the click and go SW to allow the user to do some scripting as in SPSS and SAS. On the other side, some programmers try to make the script all yourself command line environment more user friendly by building the GUI (guide user interface).

Each data analyst has its own preferences concerning the SW tools he use, however, you can be sure that you will not be able to use only one SW for all your analyses. Each analyst has the preferred tool he uses the majority of time and two or more other tools he uses in special cases. The choice of the main SW tool depends on the programmer level of the analyst and on the domain the data come from.