Description Usage Arguments Details Value See Also Examples
Given a supervised OmicsPath
object (one of
OmicsSurv
, OmicsReg
, or OmicsCateg
), extract the
first k principal components (PCs) from each pathway-subset of the
-Omics assay design matrix, test their association with the response
matrix, and return a data frame of the adjusted p-values for each
pathway.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | SuperPCA_pVals(
object,
n.threshold = 20,
numPCs = 1,
parallel = FALSE,
numCores = NULL,
adjustpValues = TRUE,
adjustment = c("Bonferroni", "Holm", "Hochberg", "SidakSS", "SidakSD", "BH", "BY",
"ABH", "TSBH"),
...
)
## S4 method for signature 'OmicsPathway'
SuperPCA_pVals(
object,
n.threshold = 20,
numPCs = 1,
parallel = FALSE,
numCores = NULL,
adjustpValues = TRUE,
adjustment = c("Bonferroni", "Holm", "Hochberg", "SidakSS", "SidakSD", "BH", "BY",
"ABH", "TSBH"),
...
)
|
object |
An object of superclass |
n.threshold |
The number of bins into which to split the feature scores
in the fit object returned internally by the |
numPCs |
The number of PCs to extract from each pathway. Defaults to 1. |
parallel |
Should the computation be completed in parallel? Defaults to
|
numCores |
If |
adjustpValues |
Should you adjust the p-values for multiple comparisons? Defaults to TRUE. |
adjustment |
Character vector of procedures. The returned data frame
will be sorted in ascending order by the first procedure in this vector,
with ties broken by the unadjusted p-value. If only one procedure is
selected, then it is necessarily the first procedure. See the documentation
for the |
... |
Dots for additional internal arguments. |
This is a wrapper function for the pathway_tScores
,
pathway_tControl
, OptimGumbelMixParams
,
GumbelMixpValues
, and TabulatepValues
functions.
Please see our Quickstart Guide for this package: https://gabrielodom.github.io/pathwayPCA/articles/Supplement1-Quickstart_Guide.html
A data frame with columns:
pathways
: The names of the pathways in the Omics*
object (given in object@trimPathwayCollection$pathways
.)
setsize
: The number of genes in each of the original
pathways (given in the object@trimPathwayCollection$setsize
object).
terms
: The pathway description, as given in the
object@trimPathwayCollection$TERMS
object.
rawp
: The unadjusted p-values of each pathway.
...
: Additional columns as specified through the
adjustment
argument.
The data frame will be sorted in ascending order by the method specified
first in the adjustment
argument. If adjustpValues = FALSE
,
then the data frame will be sorted by the raw p-values. If you have
the suggested tidyverse
package suite loaded, then this data frame
will print as a tibble
. Otherwise, it will print as
a data frame.
CreateOmics
; TabulatepValues
;
pathway_tScores
; pathway_tControl
;
OptimGumbelMixParams
; GumbelMixpValues
;
clusterApply
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ### Load the Example Data ###
data("colonSurv_df")
data("colon_pathwayCollection")
### Create an OmicsSurv Object ###
colon_OmicsSurv <- CreateOmics(
assayData_df = colonSurv_df[, -(2:3)],
pathwayCollection_ls = colon_pathwayCollection,
response = colonSurv_df[, 1:3],
respType = "surv"
)
### Calculate Pathway p-Values ###
colonSurv_superpc <- SuperPCA_pVals(
object = colon_OmicsSurv,
parallel = TRUE,
numCores = 2,
adjustpValues = TRUE,
adjustment = c("Hoch", "SidakSD")
)
|
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