GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data

doi:10.1186/1748-7188-2-5

Algorithms for Molecular Biology

Volume 2

Viewing options:

Abstract
Full text
PDF (402KB)
Additional files

Associated material:

Related literature:

Articles citing this article
on BioMed Central
on Google Scholar
on ISI Web of Science
on PubMed Central
Other articles by authors
on Google Scholar

Kadota K
Araki R
Nakai Y
Abe M

on PubMed

Kadota K
Araki R
Nakai Y
Abe M
Related articles/pages
on Google

on Google Scholar

on PubMed

Tools:

Post to:

Research

GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data

Koji Kadota¹ , Ryoko Araki² , Yuji Nakai¹ and Masumi Abe²

¹Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan

²Transcriptome Research Center, National Institute of Radiological Sciences (NIRS), 9-1, Anagawa-4-chome, Chiba-shi 263-8555, Japan

author email corresponding author email

Algorithms for Molecular Biology 2007, 2:5doi:10.1186/1748-7188-2-5


Published:	30 May 2007

Additional files

Additional File 1:

Expression data for 10,624 valid TDFs. Peak heights after GOGOTnormH for 10,624 valid TDFs are provided. It also contains two statistics measured by GOGOTstat and a t-like statistic and their ranks.

Format: XLS Size: 3.3MB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional File 2:

Expression patterns of top six TDFs ranked by a t-like statistic. Legends are the same as given in Fig. 5.

Format: PNG Size: 13KB Download file