Introduction of GODiff2

 

GODiff2 tools and datasets will be gradually released. Aimed at providing an integrated resource for EST-based transcriptomic analysis, an expanded version of GODiff-GODiff2 will be gradually released. We do not intend to update the GODiff program but to expand it to a package with multiple programs and data files, therefore the old program of GODiff will retain and all the data files can be used in both of the versions.

This version will include:

1. An alternative version of GODiff data file.

Formerly, the GODiff data files consist of expression profiles and GO associations of 5 model organisms, and the GO annotation is accurate but biased for cross-species comparisons. The new alternative data file expand the data to all the Unigene sets of 72 species (Aug. 3rd,2006).

The Unigene-GO association file of GODiff is generated through gene to Unigene mapping and protein to Unigene mapping, thus the associations are more accurate compared with GO associations generated from BLAST search. Such an approach greatly restricts the application of GODiff for only 5 organisms have GO associations to be obtained. The second drawback of the former approach is its strong bias between different species. For these two reasons, we provided an alternative data file consisting Unigenes for all species. In this data file, Unigene-GO association is generated through BLAST against the SWISSPROT protein database using GoPipe2 (e-value cutoff IE-05, first top hit, see below).

Since the GODiff program retains in GODiff2, both of the two GO associations files (generated from mapping and BLAST searching) can be used in GODiff or GODiff2 and will be updated persistently. In addition, the GO association file may be useful for those need Unigene-GO mapping for other purposes.

2. GoPipe2(coming soon).

3. Other tools for Unigene based expressional analysis (will be gradually released).

 

Citation: If you download or use GODiff, please cite us in the following way:

Zuozhou Chen, Weilin Wang, Xuefeng Bruce Ling, Jane Jijun Liu, Liangbiao Chen: GODiff: Mining functional differentiation between EST-based transcriptomes. BMC Bioinformatics, 2006, 7(1):72

Please feel free to contact Zuozhou Chen (zzchen@genetics.ac.cn) for any question.