Data analysis methods for locating entities of interest within large, multivariable datasets

The present invention provides data analysis methods for the rapid location of subsets of large, multivariable biological datasets that are of most interest for further analysis, for the investigation of molecular modes of action of biological phenomena of interest, and for the identification of sets of data points that best distinguish between experimental groups in larger datasets as putative biomarkers. While existing methods for analyzing large biological datasets generally provide too much information to the user, or not enough, the methods of the present invention entail taking user input on what kinds of trends are of interest and then finding results that match the designated trend. In such manner, the methods of the invention allow a user to quickly pinpoint the subset of data of most interest without a concomitant loss of a large percentage of relevant information, as is typical with standard methods. The methods of the invention allow for identification of molecular entities that are involved in a biological phenomenon of interest, entities that may have otherwise gone undiscovered in a large, multivariable dataset.