使用的是来自eggNog的注释信息
    目前没有相关的可公开的数据，欢迎有这种数据的小伙伴联系我。
    image.png

    1. ## 安装
    2. devtools::install_github("xiayh17/RNAseqStat2")
    4. ## 载入
    5. library(RNAseqStat2)
    7. ## 读取count矩阵
    8. row_counts <- read.delim("count_data.txt", row.names=1)
    10. ## 分组信息
    11. group_list <- c("C","C","C","I","I","I")
    13. ## 读取注释数据
    14. anno_data <- data.table::fread("out.emapper.annotations",skip = 4,fill = T)
    15. ## GO
    16. GO_anno <- eggnogG2T(anno_data,"#query","GOs")
    17. ## 获取GO Term的描述信息
    18. GO_description <- clusterProfiler::go2term(GO_anno$Term)
    20. ## KEGG
    21. KEGG_anno <- eggnogG2T(anno_data,"#query","KEGG_Pathway")
    22. KEGG_anno <- KEGG_anno %>%
    23.   filter(stringr::str_detect(Term, 'ko'))
    24. ## 获取KEGG的描述信息
    25. KEGG_description <- clusterProfiler::ko2name(KEGG_anno$Term)
    27. data_i <- Create_DEGContainer(expMatrix = row_counts,
    28.                               groupInfo = group_list,
    29.                               caseGroup = "C",
    30.                               idType = "SYMBOL",
    31.                               species = "unknow",
    32.                               GOTERM2GENE = GO_anno,
    33.                               GOTERM2NAME = GO_description,
    34.                               KEGGTERM2GENE = KEGG_anno,
    35.                               KEGGTERM2NAME = KEGG_description)
    36. ## 一键全部
    37. data_o <- runALL(object = data_i,dir = "output_test",GO = TRUE,KEGG = TRUE)
    39. ## 分步运行
    40. runCheck(data_i,"test_check")
    41. data_g <- runDEG(obj = data_i, parallel = T,dir = "test_deg")#
    42. data_h <- runHyper(obj = data_g,dir = "test_hyper",GO = TRUE,KEGG = TRUE)
    43. data_gse <- runGSEA(obj = data_h,dir = "test_gse",GO = TRUE,KEGG=TRUE)