geneSetSummaryByGenes | R Documentation |
This function creates a geneset by feature table with geneset membership
information for the features
specified by the user. Only the gene sets that
have any of the features
are included in the table returned.
geneSetSummaryByGenes(
x,
features,
with.features = TRUE,
feature.rename = NULL,
...,
as.dt = FALSE
)
## S4 method for signature 'GeneSetDb'
geneSetSummaryByGenes(
x,
features,
with.features = TRUE,
feature.rename = NULL,
...,
as.dt = FALSE
)
## S4 method for signature 'SparrowResult'
geneSetSummaryByGenes(
x,
features,
with.features = TRUE,
feature.rename = NULL,
method = NULL,
max.p = 0.3,
p.col = c("padj", "padj.by.collection", "pval"),
...,
as.dt = FALSE
)
x |
|
features |
a character vector of featureIds |
with.features |
Include columns for |
feature.rename |
if |
... |
pass through arguments |
as.dt |
If |
method |
The GSEA method to pull statistics from |
max.p |
the maximum p-value from the analysis |
p.col |
which p-value column to select from: |
a data.frame of geneset <-> feature incidence/feature matrix.
geneSetSummaryByGenes(SparrowResult)
: get geneset:feature incidence table from
a SparrowResult, optionally filtered by statistical significance from
a given gsea method
vm <- exampleExpressionSet(do.voom=TRUE)
gdb <- conform(exampleGeneSetDb(), vm)
mg <- seas(vm, gdb, design = vm$design, contrast = 'tumor')
features <- c("55839", "8522", "29087")
gsm.hit <- geneSetSummaryByGenes(gdb, features)
gsm.fid <- geneSetSummaryByGenes(mg, features, feature.rename=NULL)
gsm.sym <- geneSetSummaryByGenes(mg, features, feature.rename='symbol')
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