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    GO Kegg分析

    RNA-Seq数据分析
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    • A
      anneng 最后由 编辑

      https://ucdavis-bioinformatics-training.github.io/2018-June-RNA-Seq-Workshop/friday/enrichment.html

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      • A
        anneng 最后由 编辑

        https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/goenrichment/tutorial.html

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        • A
          anneng 最后由 编辑

          https://yulab-smu.top/biomedical-knowledge-mining-book/index.html

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          • A
            anneng 最后由 编辑

            https://advaitabio.com/faq-items/understanding-gene-ontology/

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            • A
              anneng 最后由 编辑

              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
              2a0c4ab0-30b7-4af0-9d6c-63a4366e4cbd-image.png

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              • A
                anneng 最后由 anneng 编辑

                https://advaitabio.com/faq-items/understanding-gene-ontology/
                对GO 的解释
                4b0ba8a2-b85b-4dde-8289-6426a190d484-image.png
                GO是一个DAG
                这个竞品做的还是比较好的 有个视频

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                • A
                  anneng 最后由 编辑

                  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

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                  • A
                    anneng 最后由 编辑

                    https://www.biostars.org/p/201481/#289329
                    GSEA vs GO enrich

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                    • A
                      anneng 最后由 编辑

                      可视化:
                      https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2960-9
                      https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2533-3

                      http://aegis.stanford.edu/

                      https://genomebiology.biomedcentral.com/articles/10.1186/gb-2003-4-9-r60
                      DAVID: Database for Annotation, Visualization, and Integrated Discovery
                      https://david.ncifcrf.gov/

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                      • A
                        anneng 最后由 编辑

                        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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                          anneng 最后由 anneng 编辑

                          https://biit.cs.ut.ee/gprofiler/gost
                          https://academic.oup.com/nar/article/47/W1/W191/5486750

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                          • A
                            anneng 最后由 编辑

                            http://combio-sifbi.org/GeneCloudOmics/
                            https://github.com/buithuytien/GeneCloudOmics
                            看看这个工具如何和我们集成

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