Table of Contents
KEGG database #
KEGG는 Kyoto Encyclopedia of Genes and Genomes의 약자로 pathway 관련 데이터베이스이다. 자세한 설명은 위키백과를 참고한다.
Integrate gene and metabolites expression on KEGG maps #
Usually while working with novel/new species, mostly we face the problem of data interpretations with established frame work for model organism. Mostly we all are trying to draw the miniature of homologues species. Still, there is no specific tool to make this analysis. So here I tried to connect the BLAST2GO (Annotation Tool) and PathView (Integrate Gene and metabolite expressions)
Blast2Go(유전자 기능 분석/Blast2GO): #
Blast2GO view: #
In figure 1, the blast2go will give the list of maps from KEGG databased for your given data. Based on that reference map id you can draw your desire pathway diagrams by using pathView.
Blast2GO downloded pathway map: #
Pathview is an R package, which developed for integrate the gene expression data (microarray/ RNA-seq) and metabolites on the KEGG pathway maps. Mostly focused for non-model organism
Pathview provides strong support for data integration.
It works with:
1) Essentially all types of biological data mappable to pathways,
2) Over 10 types of gene or protein IDs, and 20 types of compound or metabolite IDs,
3) Pathways for about 3000 species as well as KEGG orthology,
4) Varoius data attributes and formats, i.e. continuous/discrete data, matrices/vectors, single/multiple samples etc.
Pathview works in four steps: Downloader --> Parser -->Mapper -->Viewer
Commands to fetch the pathway map from KEGG and map the gene and component #
>sim.cpd.data=sim.mol.data(mol.type="cpd", nmol=3000) > data(cpd.simtypes) > pv.out <- pathview(gene.data = gse16873.d[, 1], cpd.data = sim.cpd.data, pathway.id = "00640", species = "hsa", out.suffix = "gse16873.cpd", keys.align = "y", kegg.native = T, key.pos = demo.paths$kpos1[i])
In the commands
Pathways id is map00640: Propanate Metabolism
Organism : Human
Data set : Control vs tumor ( all taken form the demo data which give by author)
Integrated Pathway view (Gene + metabolite) #
Here you can make differnt graphs as in reference
2) Weijun Luo1 and Cory Brouwer, Pathview: an R/Bioconductor package for pathway-based data integration and visualization, 2013, Bionformatics.