The characteristic direction: a geometrical approach to identify differentially expressed genes

2014209 citationsJournal Articlegold Open Access

Authors

Neil R. Clark · Icahn School of Medicine at Mount Sinai

Kevin Hu · Icahn School of Medicine at Mount Sinai

Axel S. Feldmann · Icahn School of Medicine at Mount Sinai

Yan Kou · Icahn School of Medicine at Mount Sinai

Edward Y. Chen · Icahn School of Medicine at Mount Sinai

Qiaonan Duan · Icahn School of Medicine at Mount Sinai

Avi Ma’ayan

Abstract

The application of the Characteristic Direction method may shed new light on relevant biological mechanisms that would have remained undiscovered by the current state-of-the-art DEG methods. The method is freely accessible via various open source code implementations using four popular programming languages: R, Python, MATLAB and Mathematica, all available at: http://www.maayanlab.net/CD.

Topics & Keywords

Gene expression and cancer classification Genomics and Chromatin Dynamics Molecular Biology Techniques and Applications

Publication Details

Published in: BMC Bioinformatics

Volume 15, Issue 1, pp. 79-79

DOI: 10.1186/1471-2105-15-79

Field-Weighted Citation Impact: 5.27

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The characteristic direction: a geometrical approach to identify differentially expressed genes

Authors

Abstract

Topics & Keywords

Publication Details