Computer ScienceBiology

GoPipe: Streamlined Gene Ontology annotation for batch anonymous sequences with statistics

Zz Chen, Chenghai Xue, S. Zhu, F. Zhou, X. Ling, Guo-Ping Liu, Liangbiao Chen

2005.2.1PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS

tlooto Summary

GoPipe is a standalone package that integrates BLAST and InterProScan results to obtain Gene Ontology annotation with built-in statistical options and is an ideal tool for streamlined GO annotation for batch sequences.

Abstract

Accelerated availability of new sequences, especially ESTs, calls for computational methods to link sequences with Gene Ontology (GO) terms in a batch mode. There is currently no program for such purpose except Goblet, an online tool which uses BLAST to interpret query sequence with proper GO terms, but has a restriction of upload sequence files less than 100 kilobytes in size. GoPipe is a standalone package that integrates BLAST and InterProScan results to obtain Gene Ontology annotation with built-in statistical options. GoPipe takes any number of BLAST and/or InterProScan output files simultaneously and launches jobs sequentially to perform parsing, data integration, redundancy removal, GO distributions calculation and graphic display. A very high annotation specificity of 99.1% was achieved for a test dataset when the program was run in the "intersection" mode, which intersects the BLAST and InterProScan results, outperforming the specificity (81.1%) obtained from the InterProScan only. Statistical tools are also provided to compare GO distributions between different inputs, so that GO distributions of different sets of batch sequences can be compared, and differentially represented GO terms can be easily displayed. High specificity, speed and flexibility make GoPipe an ideal tool for streamlined GO annotation for batch sequences. The package is freely available at http://gopipe.fishgenome.org/ or by contacting the authors.

Citation format

CHEN, Zz, et al. Gopipe: Streamlined gene ontology annotation for batch anonymous sequences with statistics. PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS, 2005, 32.