High-Dimensional Data

The goal of the ‘high-dimensional data’ topic group of the STRATOS initiative (TG9) is to provide guidance amid the jungle of opportunities and pitfalls inherent in the analysis of high-dimensional biological and medical data. Illustrative examples representing rich high-dimensional data sets presented together with in-depth evaluation and discussion of various statistical and computational approaches aim to reinforce concepts and support specific recommendations for best practices.

Subtopics receiving special emphasis include the following:

• Initial Data Analysis and pre-processing

• Exploratory Data Analysis

• Identification of informative variables

• Multiple testing

• Prediction modelling/algorithms

Many of these subtopics are also relevant to other topic groups and panels of the STRATOS initiative. Thus, in some cases, the work of TG9 will build upon their results, but always with a focus on the high-dimensional data aspect.

(link to the STRATOS Initiative webpage)