Welcome to the homepage of GEDI!

GEDI is a program that opens a new perspective to the analysis of microarray data (e.g., gene expression profiling). Unlike traditional gene clustering software, GEDI is primarily “sample-oriented” rather than “gene-oriented”. By treating each high-dimensional sample, such as one microarray experiment, as an object, it accentuates the genome-wide response of a tissue or a patient and treats it as an integrated biological entity. Hence, GEDI honors the new spirit of a “system-level” approach in biology. Yet, it also allows the researcher to quickly zoom-in from global patterns onto individual genes that exhibit interesting expression behavior and retrieve gene-specific information. Therefore, GEDI unites a novel holistic perspective with the traditional gene-centered approach in molecular biology.

GEDI allows experimental biologists or clinicians with no bioinformatics background to efficiently and intuitively navigate through a large number of expression profiles, each with a memorizable “face”, and inspect, group and collect them, like managing a stack of baseball cards.

DYNAMIC ANALYSIS: The unique strength of GEDI, for which GEDI was originally developed, is that it can display the results of parallel monitoring of multiple high-dimensional time courses, such as the comparison of expression profile time evolution in response to a series of drugs. GEDI creates animated graphics showing how 10,000s of genes change their expression over time in response to 100s of separately tested drugs.

STATIC ANAYLSIS: The signature graphical output of GEDI, the GEDI-“mosaics” provide a unique, one-glance visual engram that gives each microarray or other high-dimensional dataset a face. A characteristic of GEDI's analysis is that it does not prejudicate any particular structure in the data (such as clusters or hierarchical organization). Thus, it allows the researcher to use human pattern recognition to perform a global first-level analysis of the data.

  Papers using GEDI

 
GEDI 2.1 Screen Shot
DYNAMIC DATA
Dynamic analysis - time courses
Response to drug 1    Response to drug 2


 
STATIC DATA
Static analysis - difference calculation
      Normal             Cancer      Cancer - Normal

GEDI was developed by Gabriel Eichler, Ying Feng, Yuchun Guo and Sui Huang in the Ingber laboratory at the Children's Hospital and Harvard Medical School, Boston. The project was supported by the Air Force Office of Scientific Research and the National Health Institutes. It is distributed for free academic use by the Children’s Hospital, Boston.

Reference:
Eichler, G.S., Huang, S. Ingber, D.E., Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles, Bioinformatics, 2003;19(17),2321-2
 
Guo YC, Eichler GS, Feng Y, Ingber DE, Huang S. Towards a Holistic, Yet Gene-Centered Analysis of Gene Expression Profiles: A Case Study of Human Lung Cancers. Journal of Biomedicine and Biotechnology. 2006, Pages 1–11.
 
Huang, S, Guo YP, May G, Enver T. Bifurcation dynamics of cell fate decision in bipotent progenitor cells. Dev. Biol. 305 (2007) 695-713.
 
Chang HH, Hemberg M, Barahona M, Ingber DE, Huang S. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature. 2008 May 22;453(7194):544-7.