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YuLab-SMU/enrichplot/enrichplot/R/method-fortify.R

ID	Description	GeneRatio	BgRatio	pvalue	p.adjust	qvalue	geneID	Count
GO:0005819	spindle	26/201	313/11865	1.748160953695457e-11	5.261964470623326e-9	4.802842199100151e-9	CDCA8/CDC20/KIF23/CENPE/ASPM/DLGAP5/SKA1/NUSAP1/TPX2/TACC3/NEK2/CDK1/MAD2L1/KIF18A/BIRC5/KIF11/TRAT1/TTK/AURKB/PRC1/KIFC1/KIF18B/KIF20A/AURKA/CCNB1/KIF4A	26
GO:0000775	chromosome, centromeric region	19/201	169/11865	6.340879428793475e-11	6.8326302038778255e-9	6.236462609589483e-9	CDCA8/CENPE/NDC80/TOP2A/HJURP/SKA1/NEK2/CENPM/CENPN/ERCC6L/MAD2L1/KIF18A/CDT1/BIRC5/EZH2/TTK/NCAPG/AURKB/CCNB1	19
GO:0072686	mitotic spindle	17/201	131/11865	6.80993043575863e-11	6.8326302038778255e-9	6.236462609589483e-9	KIF23/CENPE/ASPM/SKA1/NUSAP1/TPX2/TACC3/CDK1/MAD2L1/KIF18A/KIF11/TRAT1/AURKB/PRC1/KIFC1/KIF18B/AURKA	17
GO:0000779	condensed chromosome, centromeric region	16/201	123/11865	2.4398133262121816e-10	1.8359595279746667e-8	1.675766521424683e-8	CENPE/NDC80/HJURP/SKA1/NEK2/CENPM/CENPN/ERCC6L/MAD2L1/KIF18A/CDT1/BIRC5/TTK/NCAPG/AURKB/CCNB1	16
GO:0098687	chromosomal region	23/201	287/11865	5.709915237613229e-10	3.437368973043164e-8	3.1374481621411644e-8	CDCA8/CENPE/NDC80/TOP2A/HJURP/SKA1/NEK2/CENPM/RAD51AP1/CENPN/CDK1/ERCC6L/MAD2L1/KIF18A/CDT1/BIRC5/EZH2/TTK/NCAPG/AURKB/CHEK1/CCNB1/MCM5	23
GO:0000776	kinetochore	15/201	115/11865	8.719736637953852e-10	4.3744012133735155e-8	3.992721513168343e-8	CENPE/NDC80/HJURP/SKA1/NEK2/CENPM/CENPN/ERCC6L/MAD2L1/KIF18A/CDT1/BIRC5/TTK/AURKB/CCNB1	15

dotplot函数中使用as.data.frame(res <- as.data.frame(model))的泛型函数将enrichResult对象转换为data.frame对象，这其中就使用了enrichGO(pvalueCutoff = 0.01) 函数中pvalueCutoff参数设置的阈值对p.agjust进行筛选。res <- res[!is.na(res$Description), ]也是一个泛型函数，

点击查看S3对象的泛型和多态

fortify.internal

res <- as.data.frame(model)
res <- res[!is.na(res$Description), ]

`res <- as.data.frame(model)`

##' @method as.data.frame gseaResult
##' @export
as.data.frame.enrichResult <- function(x, ...) {
    x <- get_enriched(x)
    as.data.frame(x@result, ...)
}

`res <- res[!is.na(res$Description), ]`

##' @method [ enrichResult
##' @export
`[.enrichResult` <- function(x, i, j, asis = FALSE, ...) {
    x <- get_enriched(x)
    y <- x@result[i, j, ...]
    if (!asis)
        return(y)
    x@result <- y
    return(x)
}

`x <- get_enriched(x)`

get_enriched <- function(object) {
    Over <- object@result
    pvalueCutoff <- object@pvalueCutoff
    if (length(pvalueCutoff) != 0) {
        ## if groupGO result, numeric(0)
        Over <- Over[ Over$pvalue <= pvalueCutoff, ]
        Over <- Over[ Over$p.adjust <= pvalueCutoff, ]
    }
    qvalueCutoff <- object@qvalueCutoff
    if (length(qvalueCutoff) != 0) {
        if (! any(is.na(Over$qvalue))) {
            if (length(qvalueCutoff) > 0)
                Over <- Over[ Over$qvalue <= qvalueCutoff, ]
        }
    }
    object@result <- Over
    return(object)
}

可以看到pvalueCutoff <- object@pvalueCutoff这行代码是获取了enrichResult对象的pvalueCutoff这个属性。

Over <- Over[ Over$pvalue <= pvalueCutoff, ]
Over <- Over[ Over$p.adjust <= pvalueCutoff, ]

这里直接就使用了p.adjust < = pvalueCutoff的阈值进行过滤，并没有使用pvalue进行过滤的选项。

更改后的R包
BioinfoFungi/enrichplot2