diff --git a/data_analysis/enrichment_mm.Rmd b/data_analysis/enrichment_mm.Rmd index d79d593..09d1ac4 100644 --- a/data_analysis/enrichment_mm.Rmd +++ b/data_analysis/enrichment_mm.Rmd @@ -123,6 +123,9 @@ Next, we use Fisher's exact test to test for GO enrichment among significantly D Create topGOdata object: ```{r} +geneList <- DE.nodupENTREZ$adj.P.Val +names(geneList) <- DE.nodupENTREZ$ENTREZID + # Create topGOData object GOdata <- new("topGOdata", ontology = "BP", diff --git a/data_analysis/enrichment_mm_with_quizzes.Rmd b/data_analysis/enrichment_mm_with_quizzes.Rmd index dc6bcbd..a5fba18 100644 --- a/data_analysis/enrichment_mm_with_quizzes.Rmd +++ b/data_analysis/enrichment_mm_with_quizzes.Rmd @@ -196,6 +196,9 @@ Next, we use Fisher's exact test to test for GO enrichment among significantly D Create topGOdata object: ```{r} +geneList <- DE.nodupENTREZ$adj.P.Val +names(geneList) <- DE.nodupENTREZ$ENTREZID + # Create topGOData object GOdata <- new("topGOdata", ontology = "BP", diff --git a/data_analysis/enrichment_mm_with_quizzes.md b/data_analysis/enrichment_mm_with_quizzes.md index 5132b39..39e1032 100644 --- a/data_analysis/enrichment_mm_with_quizzes.md +++ b/data_analysis/enrichment_mm_with_quizzes.md @@ -448,6 +448,9 @@ Next, we use Fisher's exact test to test for GO enrichment among significantly D Create topGOdata object: ``` r +geneList <- DE.nodupENTREZ$adj.P.Val +names(geneList) <- DE.nodupENTREZ$ENTREZID + # Create topGOData object GOdata <- new("topGOdata", ontology = "BP", @@ -493,7 +496,7 @@ resultFisher <- runTest(GOdata, algorithm = "elim", statistic = "fisher") ## ## -- Elim Algorithm -- ## -## the algorithm is scoring 13301 nontrivial nodes +## the algorithm is scoring 13091 nontrivial nodes ## parameters: ## test statistic: fisher ## cutOff: 0.01 @@ -511,87 +514,87 @@ resultFisher <- runTest(GOdata, algorithm = "elim", statistic = "fisher") ``` ## -## Level 17: 49 nodes to be scored (12 eliminated genes) +## Level 17: 46 nodes to be scored (12 eliminated genes) ``` ``` ## -## Level 16: 85 nodes to be scored (12 eliminated genes) +## Level 16: 82 nodes to be scored (22 eliminated genes) ``` ``` ## -## Level 15: 119 nodes to be scored (81 eliminated genes) +## Level 15: 116 nodes to be scored (77 eliminated genes) ``` ``` ## -## Level 14: 248 nodes to be scored (106 eliminated genes) +## Level 14: 244 nodes to be scored (102 eliminated genes) ``` ``` ## -## Level 13: 551 nodes to be scored (268 eliminated genes) +## Level 13: 536 nodes to be scored (277 eliminated genes) ``` ``` ## -## Level 12: 993 nodes to be scored (400 eliminated genes) +## Level 12: 973 nodes to be scored (538 eliminated genes) ``` ``` ## -## Level 11: 1502 nodes to be scored (1753 eliminated genes) +## Level 11: 1460 nodes to be scored (2064 eliminated genes) ``` ``` ## -## Level 10: 1790 nodes to be scored (2196 eliminated genes) +## Level 10: 1760 nodes to be scored (2215 eliminated genes) ``` ``` ## -## Level 9: 1964 nodes to be scored (2961 eliminated genes) +## Level 9: 1924 nodes to be scored (3237 eliminated genes) ``` ``` ## -## Level 8: 1901 nodes to be scored (3821 eliminated genes) +## Level 8: 1879 nodes to be scored (3919 eliminated genes) ``` ``` ## -## Level 7: 1672 nodes to be scored (4689 eliminated genes) +## Level 7: 1659 nodes to be scored (4558 eliminated genes) ``` ``` ## -## Level 6: 1252 nodes to be scored (5645 eliminated genes) +## Level 6: 1246 nodes to be scored (5649 eliminated genes) ``` ``` ## -## Level 5: 682 nodes to be scored (6903 eliminated genes) +## Level 5: 678 nodes to be scored (6209 eliminated genes) ``` ``` ## -## Level 4: 339 nodes to be scored (8294 eliminated genes) +## Level 4: 334 nodes to be scored (7481 eliminated genes) ``` ``` ## -## Level 3: 110 nodes to be scored (9426 eliminated genes) +## Level 3: 110 nodes to be scored (8857 eliminated genes) ``` ``` ## -## Level 2: 18 nodes to be scored (9444 eliminated genes) +## Level 2: 18 nodes to be scored (8857 eliminated genes) ``` ``` ## -## Level 1: 1 nodes to be scored (11119 eliminated genes) +## Level 1: 1 nodes to be scored (10926 eliminated genes) ``` ``` r @@ -602,19 +605,19 @@ head(tab) ``` ## GO.ID Term -## 1 GO:0045944 positive regulation of transcription by RNA polymerase II -## 2 GO:0032731 positive regulation of interleukin-1 beta production -## 3 GO:0051241 negative regulation of multicellular organismal process +## 1 GO:0032731 positive regulation of interleukin-1 beta production +## 2 GO:0045944 positive regulation of transcription by RNA polymerase II +## 3 GO:1901224 positive regulation of non-canonical NF-kappaB signal transduction ## 4 GO:0001525 angiogenesis -## 5 GO:0042742 defense response to bacterium -## 6 GO:1901224 positive regulation of non-canonical NF-kappaB signal transduction +## 5 GO:0051607 defense response to virus +## 6 GO:0042742 defense response to bacterium ## Annotated Significant Expected raw.p.value -## 1 890 635 571.68 1.9e-06 -## 2 61 55 39.18 3.7e-06 -## 3 840 623 539.56 8.3e-06 -## 4 381 283 244.73 1.4e-05 -## 5 206 160 132.32 1.9e-05 -## 6 54 48 34.69 3.9e-05 +## 1 61 53 35.90 1.8e-06 +## 2 890 589 523.85 2.0e-06 +## 3 54 47 31.78 6.5e-06 +## 4 381 272 224.26 6.6e-06 +## 5 263 193 154.80 1.9e-05 +## 6 206 154 121.25 2.1e-05 ``` * Annotated: number of genes (in our gene list) that are annotated with the term * Significant: Number of significantly DE genes annotated with that term (i.e. genes where geneList = 1)