KOBAS identify 3.0.3


KEGG Orthology Based Annotation System (KOBAS) is a standalone Python application in Bioinformatics. KOBAS can assign appropriate KO terms for queried sequences based on similarity search, and it can further discover
enriched KO terms among the annotation results by frequency of pathways or statistical significance of pathways.

Quick Start

Test Data


Test data for this app appears directly in the Discovery Environment in the Data window under Community Data -> iplantcollaborative -> example_data -> KOBAS -> identify

Input File(s)

Use  from the directory above as test input.

use kobas_annoate_out.txt as the input file

Parameters Used in App

Use the these parameters with test data:

use 'dme' as the background (Species codes can be looked up here: https://www.kegg.jp/kegg/catalog/org_list.html)

Output File(s)

sqlite3–contains the database files used to annotate your data

  • dme.db
  • organism.db

KOBAS identify output.txt

Tool Source for App