kg is a simple Python CLI and API that enables retrieving KEGG pathways, their definitions and their related genes.
It is tested on both Python 2.7 and Python 3+.
# 0.0.11 (1.12.2017)
- Fix bug due to underlying API changes
# 0.0.10 (01.04.2016)
- Fix error when input file only contains one line.
- Change cache dir to ~/.joblib/kegg
# 0.0.8 (06.11.2015)
- Fix sort bug
- Now uses entrezgene instead of ambiguous gene names.
- Add version info (kg -v).
kg
Get KEGG data from the command line.
(Visit github.com/endrebak/kg for examples and help.)
Usage:
kg --help
kg --version
kg --mergecol=COL --species=SPEC [--genes] [--definitions] [--noheader] FILE
kg --species=SPEC
kg --removecache
Arguments:
FILE infile to add KEGG data to (read STDIN with -)
-s SPEC --species=SPEC name of species (examples: hsa, mmu, rno...)
-m COL --mergecol=COL column (0-indexed int or name) containing gene names
Options:
-h --help show this message
-v --version show version info
-n --noheader the input data does not contain a header
-d --definitions add KEGG pathway definitions to the output
-g --genes get the genes related to KEGG pathways
(when used, mergecol COL should contain KEGG pathway
ids)
--removecache removes the local cache so that the KEGG REST DB is
accessed anew
kg -s rno -d | head
Cache path is: /Users/endrebakkenstovner/.kegg/ (Time: Thu, 05 Nov 2015 20:00:43 )
kegg_pathway entrezgene kegg_pathway_definition
00010 100145871 Glycolysis / Gluconeogenesis
00010 100364027 Glycolysis / Gluconeogenesis
00010 100364062 Glycolysis / Gluconeogenesis
00010 100911515 Glycolysis / Gluconeogenesis
00010 100911625 Glycolysis / Gluconeogenesis
00010 114508 Glycolysis / Gluconeogenesis
00010 117098 Glycolysis / Gluconeogenesis
00010 171178 Glycolysis / Gluconeogenesis
00010 24172 Glycolysis / GluconeogenesisAs you can see above:
- When several pathways are associated with a gene, that gene row is duplicated
kgsupportsR style ".tsv"files where the index column lacks a header
from kegg.lib import get_kegg_data
pathway_definitions = True
df = get_kegg_data("rno", pathway_definitions)
df.head(5)
# Output
# kegg_pathway entrezgene kegg_pathway_definition
# 0 00010 100145871 Glycolysis / Gluconeogenesis
# 1 00010 100364027 Glycolysis / Gluconeogenesis
# 2 00010 100364062 Glycolysis / Gluconeogenesis
# 3 00010 100911515 Glycolysis / Gluconeogenesis
# 4 00010 100911625 Glycolysis / Gluconeogenesispip install kg