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유전자 기능 분석 KEGG #
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Structured data

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Database

KEGG database #

KEGG는 Kyoto Encyclopedia of Genes and Genomes의 약자로 분자 수준 정보, sequencing으로 생성된 분자 데이터로부터 세포, 생물 및 생태계와 같은 biological system의 유틸리티를 예측할 때 사용되는 데이터베이스이다. KEGG database를 활용하면 알려진 효소에 mapping하여 pathway 분석을 할 수 있으며, 물질대사, 환경적 경로, 유전적 경로 등의 pathway로 나뉜다. 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 OmicsBox (Annotation Tool) and PathView (Integrate Gene and metabolite expressions)

OmicsBox #

이전까지 KEGG pathway 분석을 하기 위해 가장 많이 이용되는 software는 BioBam사의 Blast2GO였지만, Blast2Go가 OmicsBox로 리뉴얼되면서 OmicsBox Functional Analysis 부분에 흡수되었다.

OmicsBox KEGG pathway view: #

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Pathview: #

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

KEGG pathway 예제: #

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References: #

1) Vedio http://www.youtube.com/watch?v=sne_Nb9au20

2) Weijun Luo1 and Cory Brouwer, Pathview: an R/Bioconductor package for pathway-based data integration and visualization, 2013, Bionformatics.

3) https://www.genome.jp/kegg/

4) SCH

Suggested Pages #

0.0.1_20140628_0