viper: VIPER
In viper: Virtual Inference of Protein-activity by Enriched Regulon analysis
Description
Usage
Arguments
Value
See Also
Examples
Description
This function performs Virtual Inference of Protein-activity by Enriched Regulon analysis
Usage
1
2
3
4
5
6
viper(eset, regulon, dnull = NULL, pleiotropy = FALSE, nes = TRUE,
method = c("none", "scale", "rank", "mad", "ttest"), bootstraps = 0,
minsize = 25, adaptive.size = FALSE, eset.filter = TRUE,
mvws = 1, pleiotropyArgs = list(regulators = 0.05, shadow = 0.05,
targets = 10, penalty = 20, method = "adaptive"), cores = 1,
verbose = TRUE)
Arguments
eset
ExpressionSet object or Numeric matrix containing the expression data or gene expression signatures, with samples in columns and genes in rows
regulon
Object of class regulon or list of objects of class regulon for metaVIPER analysis
dnull
Numeric matrix for the null model, usually generated by nullTtest
pleiotropy
Logical, whether correction for pleiotropic regulation should be performed
nes
Logical, whether the enrichment score reported should be normalized
method
Character string indicating the method for computing the single samples signature, either scale, rank, mad, ttest or none
bootstraps
Integer indicating the number of bootstraps iterations to perform. Only the scale method is implemented with bootstraps.
minsize
Integer indicating the minimum number of targets allowed per regulon
adaptive.size
Logical, whether the weighting scores should be taken into account for computing the regulon size
eset.filter
Logical, whether the dataset should be limited only to the genes represented in the interactome
#' @param mvws Number or vector indicating either the exponent score for the metaViper weights, or the inflection point and trend for the sigmoid function describing the weights in metaViper
pleiotropyArgs
list of 5 numbers for the pleotropy correction indicating: regulators p-value threshold, pleiotropic interaction p-value threshold, minimum number of targets in the overlap between pleiotropic regulators, penalty for the pleiotropic interactions and the method for computing the pleiotropy, either absolute or adaptive
cores
Integer indicating the number of cores to use (only 1 in Windows-based systems)
verbose
Logical, whether progression messages should be printed in the terminal
Value
A matrix of inferred activity for each regulator gene in the network across all samples
See Also
Examples
1
2
3
4
5
6
7
8
Example output
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: ‘BiocGenerics’
The following objects are masked from ‘package:parallel’:
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from ‘package:stats’:
IQR, mad, sd, var, xtabs
The following objects are masked from ‘package:base’:
anyDuplicated, append, as.data.frame, basename, cbind, colnames,
dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Computing the association scores
Computing regulons enrichment with aREA
|
| | 0%
|
| | 1%
|
|= | 1%
|
|= | 2%
|
|== | 2%
|
|== | 3%
|
|== | 4%
|
|=== | 4%
|
|=== | 5%
|
|==== | 5%
|
|==== | 6%
|
|===== | 6%
|
|===== | 7%
|
|===== | 8%
|
|====== | 8%
|
|====== | 9%
|
|======= | 9%
|
|======= | 10%
|
|======= | 11%
|
|======== | 11%
|
|======== | 12%
|
|========= | 12%
|
|========= | 13%
|
|========= | 14%
|
|========== | 14%
|
|========== | 15%
|
|=========== | 15%
|
|=========== | 16%
|
|============ | 17%
|
|============ | 18%
|
|============= | 18%
|
|============= | 19%
|
|============== | 19%
|
|============== | 20%
|
|============== | 21%
|
|=============== | 21%
|
|=============== | 22%
|
|================ | 22%
|
|================ | 23%
|
|================ | 24%
|
|================= | 24%
|
|================= | 25%
|
|================== | 25%
|
|================== | 26%
|
|=================== | 27%
|
|=================== | 28%
|
|==================== | 28%
|
|==================== | 29%
|
|===================== | 29%
|
|===================== | 30%
|
|===================== | 31%
|
|====================== | 31%
|
|====================== | 32%
|
|======================= | 32%
|
|======================= | 33%
|
|======================== | 34%
|
|======================== | 35%
|
|========================= | 35%
|
|========================= | 36%
|
|========================== | 37%
|
|========================== | 38%
|
|=========================== | 38%
|
|=========================== | 39%
|
|============================ | 39%
|
|============================ | 40%
|
|============================ | 41%
|
|============================= | 41%
|
|============================= | 42%
|
|============================== | 42%
|
|============================== | 43%
|
|=============================== | 44%
|
|=============================== | 45%
|
|================================ | 45%
|
|================================ | 46%
|
|================================= | 47%
|
|================================= | 48%
|
|================================== | 48%
|
|================================== | 49%
|
|=================================== | 49%
|
|=================================== | 50%
|
|=================================== | 51%
|
|==================================== | 51%
|
|==================================== | 52%
|
|===================================== | 52%
|
|===================================== | 53%
|
|====================================== | 54%
|
|====================================== | 55%
|
|======================================= | 55%
|
|======================================= | 56%
|
|======================================== | 57%
|
|======================================== | 58%
|
|========================================= | 58%
|
|========================================= | 59%
|
|========================================== | 59%
|
|========================================== | 60%
|
|========================================== | 61%
|
|=========================================== | 61%
|
|=========================================== | 62%
|
|============================================ | 62%
|
|============================================ | 63%
|
|============================================= | 64%
|
|============================================= | 65%
|
|============================================== | 65%
|
|============================================== | 66%
|
|=============================================== | 67%
|
|=============================================== | 68%
|
|================================================ | 68%
|
|================================================ | 69%
|
|================================================= | 69%
|
|================================================= | 70%
|
|================================================= | 71%
|
|================================================== | 71%
|
|================================================== | 72%
|
|=================================================== | 72%
|
|=================================================== | 73%
|
|==================================================== | 74%
|
|==================================================== | 75%
|
|===================================================== | 75%
|
|===================================================== | 76%
|
|====================================================== | 76%
|
|====================================================== | 77%
|
|====================================================== | 78%
|
|======================================================= | 78%
|
|======================================================= | 79%
|
|======================================================== | 79%
|
|======================================================== | 80%
|
|======================================================== | 81%
|
|========================================================= | 81%
|
|========================================================= | 82%
|
|========================================================== | 82%
|
|========================================================== | 83%
|
|=========================================================== | 84%
|
|=========================================================== | 85%
|
|============================================================ | 85%
|
|============================================================ | 86%
|
|============================================================= | 86%
|
|============================================================= | 87%
|
|============================================================= | 88%
|
|============================================================== | 88%
|
|============================================================== | 89%
|
|=============================================================== | 89%
|
|=============================================================== | 90%
|
|=============================================================== | 91%
|
|================================================================ | 91%
|
|================================================================ | 92%
|
|================================================================= | 92%
|
|================================================================= | 93%
|
|================================================================= | 94%
|
|================================================================== | 94%
|
|================================================================== | 95%
|
|=================================================================== | 95%
|
|=================================================================== | 96%
|
|==================================================================== | 96%
|
|==================================================================== | 97%
|
|==================================================================== | 98%
|
|===================================================================== | 98%
|
|===================================================================== | 99%
|
|======================================================================| 99%
|
|======================================================================| 100%[1] 6249 211
GSM44075 GSM44078 GSM44080 GSM44081 GSM44082
ADA 9.571369 10.599436 8.740659 10.104469 8.918148
CDH2 6.175890 5.312704 5.651928 4.462205 4.807664
MED6 9.671113 8.773383 9.190276 9.526235 8.795248
NR2E3 9.847733 9.582061 9.628792 8.820422 9.270526
ACOT8 9.083551 9.043654 8.010374 8.683276 8.744792
Object of class regulon with 621 regulators, 6249 targets and 172240 interactions
[1] 621 211
GSM44075 GSM44078 GSM44080 GSM44081 GSM44082
AATF 7.1823382 4.642804635 7.4858308 7.0831808 6.473570
ADNP 3.4591275 1.972037051 3.3625029 4.6900031 3.415285
ADNP2 0.4334423 0.004665852 0.4110936 0.5721498 0.540023
AEBP1 -6.0201433 -3.774699249 -5.6031467 -5.0785343 -5.934232
AFF3 -1.5112415 -1.025039393 -2.6894286 -2.0569731 -1.276213
viper documentation built on Nov. 8, 2020, 7:37 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value See Also Examples
Description
This function performs Virtual Inference of Protein-activity by Enriched Regulon analysis
Usage
1 2 3 4 5 6 | viper(eset, regulon, dnull = NULL, pleiotropy = FALSE, nes = TRUE,
method = c("none", "scale", "rank", "mad", "ttest"), bootstraps = 0,
minsize = 25, adaptive.size = FALSE, eset.filter = TRUE,
mvws = 1, pleiotropyArgs = list(regulators = 0.05, shadow = 0.05,
targets = 10, penalty = 20, method = "adaptive"), cores = 1,
verbose = TRUE)
|
Arguments
eset |
ExpressionSet object or Numeric matrix containing the expression data or gene expression signatures, with samples in columns and genes in rows |
regulon |
Object of class regulon or list of objects of class regulon for metaVIPER analysis |
dnull |
Numeric matrix for the null model, usually generated by |
pleiotropy |
Logical, whether correction for pleiotropic regulation should be performed |
nes |
Logical, whether the enrichment score reported should be normalized |
method |
Character string indicating the method for computing the single samples signature, either scale, rank, mad, ttest or none |
bootstraps |
Integer indicating the number of bootstraps iterations to perform. Only the scale method is implemented with bootstraps. |
minsize |
Integer indicating the minimum number of targets allowed per regulon |
adaptive.size |
Logical, whether the weighting scores should be taken into account for computing the regulon size |
eset.filter |
Logical, whether the dataset should be limited only to the genes represented in the interactome #' @param mvws Number or vector indicating either the exponent score for the metaViper weights, or the inflection point and trend for the sigmoid function describing the weights in metaViper |
pleiotropyArgs |
list of 5 numbers for the pleotropy correction indicating: regulators p-value threshold, pleiotropic interaction p-value threshold, minimum number of targets in the overlap between pleiotropic regulators, penalty for the pleiotropic interactions and the method for computing the pleiotropy, either absolute or adaptive |
cores |
Integer indicating the number of cores to use (only 1 in Windows-based systems) |
verbose |
Logical, whether progression messages should be printed in the terminal |
Value
A matrix of inferred activity for each regulator gene in the network across all samples
See Also
Examples
1 2 3 4 5 6 7 8 |
Example output
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: ‘BiocGenerics’
The following objects are masked from ‘package:parallel’:
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from ‘package:stats’:
IQR, mad, sd, var, xtabs
The following objects are masked from ‘package:base’:
anyDuplicated, append, as.data.frame, basename, cbind, colnames,
dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Computing the association scores
Computing regulons enrichment with aREA
|
| | 0%
|
| | 1%
|
|= | 1%
|
|= | 2%
|
|== | 2%
|
|== | 3%
|
|== | 4%
|
|=== | 4%
|
|=== | 5%
|
|==== | 5%
|
|==== | 6%
|
|===== | 6%
|
|===== | 7%
|
|===== | 8%
|
|====== | 8%
|
|====== | 9%
|
|======= | 9%
|
|======= | 10%
|
|======= | 11%
|
|======== | 11%
|
|======== | 12%
|
|========= | 12%
|
|========= | 13%
|
|========= | 14%
|
|========== | 14%
|
|========== | 15%
|
|=========== | 15%
|
|=========== | 16%
|
|============ | 17%
|
|============ | 18%
|
|============= | 18%
|
|============= | 19%
|
|============== | 19%
|
|============== | 20%
|
|============== | 21%
|
|=============== | 21%
|
|=============== | 22%
|
|================ | 22%
|
|================ | 23%
|
|================ | 24%
|
|================= | 24%
|
|================= | 25%
|
|================== | 25%
|
|================== | 26%
|
|=================== | 27%
|
|=================== | 28%
|
|==================== | 28%
|
|==================== | 29%
|
|===================== | 29%
|
|===================== | 30%
|
|===================== | 31%
|
|====================== | 31%
|
|====================== | 32%
|
|======================= | 32%
|
|======================= | 33%
|
|======================== | 34%
|
|======================== | 35%
|
|========================= | 35%
|
|========================= | 36%
|
|========================== | 37%
|
|========================== | 38%
|
|=========================== | 38%
|
|=========================== | 39%
|
|============================ | 39%
|
|============================ | 40%
|
|============================ | 41%
|
|============================= | 41%
|
|============================= | 42%
|
|============================== | 42%
|
|============================== | 43%
|
|=============================== | 44%
|
|=============================== | 45%
|
|================================ | 45%
|
|================================ | 46%
|
|================================= | 47%
|
|================================= | 48%
|
|================================== | 48%
|
|================================== | 49%
|
|=================================== | 49%
|
|=================================== | 50%
|
|=================================== | 51%
|
|==================================== | 51%
|
|==================================== | 52%
|
|===================================== | 52%
|
|===================================== | 53%
|
|====================================== | 54%
|
|====================================== | 55%
|
|======================================= | 55%
|
|======================================= | 56%
|
|======================================== | 57%
|
|======================================== | 58%
|
|========================================= | 58%
|
|========================================= | 59%
|
|========================================== | 59%
|
|========================================== | 60%
|
|========================================== | 61%
|
|=========================================== | 61%
|
|=========================================== | 62%
|
|============================================ | 62%
|
|============================================ | 63%
|
|============================================= | 64%
|
|============================================= | 65%
|
|============================================== | 65%
|
|============================================== | 66%
|
|=============================================== | 67%
|
|=============================================== | 68%
|
|================================================ | 68%
|
|================================================ | 69%
|
|================================================= | 69%
|
|================================================= | 70%
|
|================================================= | 71%
|
|================================================== | 71%
|
|================================================== | 72%
|
|=================================================== | 72%
|
|=================================================== | 73%
|
|==================================================== | 74%
|
|==================================================== | 75%
|
|===================================================== | 75%
|
|===================================================== | 76%
|
|====================================================== | 76%
|
|====================================================== | 77%
|
|====================================================== | 78%
|
|======================================================= | 78%
|
|======================================================= | 79%
|
|======================================================== | 79%
|
|======================================================== | 80%
|
|======================================================== | 81%
|
|========================================================= | 81%
|
|========================================================= | 82%
|
|========================================================== | 82%
|
|========================================================== | 83%
|
|=========================================================== | 84%
|
|=========================================================== | 85%
|
|============================================================ | 85%
|
|============================================================ | 86%
|
|============================================================= | 86%
|
|============================================================= | 87%
|
|============================================================= | 88%
|
|============================================================== | 88%
|
|============================================================== | 89%
|
|=============================================================== | 89%
|
|=============================================================== | 90%
|
|=============================================================== | 91%
|
|================================================================ | 91%
|
|================================================================ | 92%
|
|================================================================= | 92%
|
|================================================================= | 93%
|
|================================================================= | 94%
|
|================================================================== | 94%
|
|================================================================== | 95%
|
|=================================================================== | 95%
|
|=================================================================== | 96%
|
|==================================================================== | 96%
|
|==================================================================== | 97%
|
|==================================================================== | 98%
|
|===================================================================== | 98%
|
|===================================================================== | 99%
|
|======================================================================| 99%
|
|======================================================================| 100%[1] 6249 211
GSM44075 GSM44078 GSM44080 GSM44081 GSM44082
ADA 9.571369 10.599436 8.740659 10.104469 8.918148
CDH2 6.175890 5.312704 5.651928 4.462205 4.807664
MED6 9.671113 8.773383 9.190276 9.526235 8.795248
NR2E3 9.847733 9.582061 9.628792 8.820422 9.270526
ACOT8 9.083551 9.043654 8.010374 8.683276 8.744792
Object of class regulon with 621 regulators, 6249 targets and 172240 interactions
[1] 621 211
GSM44075 GSM44078 GSM44080 GSM44081 GSM44082
AATF 7.1823382 4.642804635 7.4858308 7.0831808 6.473570
ADNP 3.4591275 1.972037051 3.3625029 4.6900031 3.415285
ADNP2 0.4334423 0.004665852 0.4110936 0.5721498 0.540023
AEBP1 -6.0201433 -3.774699249 -5.6031467 -5.0785343 -5.934232
AFF3 -1.5112415 -1.025039393 -2.6894286 -2.0569731 -1.276213
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.