GO Kegg分析
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https://yulab-smu.top/biomedical-knowledge-mining-book/enrichment-overview.html
对富集分析讲的比较透彻 里面提到了超几何检验
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https://advaitabio.com/faq-items/understanding-gene-ontology/
对GO 的解释
GO是一个DAG
这个竞品做的还是比较好的 有个视频 -
Statistics and Data Analysis for Microarrays Using R and Bioconductor
这本书里面讲了很多具体的数学原理 -
https://www.biostars.org/p/201481/#289329
GSEA vs GO enrich -
可视化:
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2960-9
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2533-3https://genomebiology.biomedcentral.com/articles/10.1186/gb-2003-4-9-r60
DAVID: Database for Annotation, Visualization, and Integrated Discovery
https://david.ncifcrf.gov/ -
https://www.spandidos-publications.com/10.3892/mmr.2019.10511
GO (geneontology.org) analysis, frequently used in functional enrichment studies of large-scale genes (20), and KEGG (www.genome.jp/kegg) enrichment analysis were performed to investigate the biological pathways that involve differentially expressed mRNAs. In the present study, clusterProfiler (v3.12.0; guangchuangyu.github.io/software/clusterProfiler) and Database for Annotation, Visualization and Integrated Discovery tools (v6.8; http://david.ncifcrf.gov/) were used to analyze the functional enrichment conditions for dysregulated mRNAs (21–23). The false discovery rate (FDR) was calculated to correct the P-value and FDR<0.05 was selected as the threshold for a statistically significant difference. -
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