plot.msviper: Plot msviper results
In viper: Virtual Inference of Protein-activity by Enriched Regulon analysis
Description
Usage
Arguments
Value
See Also
Examples
Description
This function generate a plot for msviper results showing the enrichment of the target genes for each significant master regulator on the gene expression signature
Usage
1
2
3
4
5
Arguments
x
msviper object produced by msviper function
mrs
Either an integer indicating the number of master regulators to include in the plot, or a character vector containing the names of the master regulators to include in the plot
color
Vector of two components indicating the colors for the negative and positive parts of the regulon
pval
Optional matrix of p-values to include in the plot
bins
Number of bins to split the vector of scores in order to compute the density color of the bars
cex
Number indicating the text size scaling, 0 indicates automatic scaling
density
Integrer indicating the number of steps for the kernel density. Zero for not ploting it
smooth
Number indicating the proportion of point for smoothing the density distribution. Zero for not using the smoother
sep
Number indicating the separation from figure and text
hybrid
Logical, whether the 3-tail approach used for computingthe enrichment should be reflected in the plot
include
Vector indicating the information to include as heatmap to the right of the msviper plot: expression and activity
gama
Positive number indicating the exponential transformation for the activity and expression color scale
...
Given for compatibility to the plot generic function
Value
Nothing, a plot is generated in the default output device
See Also
Examples
1
2
3
4
5
data(bcellViper, package="bcellViper")
sig <- rowTtest(dset, "description", c("CB", "CC"), "N")$statistic
dnull <- ttestNull(dset, "description", c("CB", "CC"), "N", per=100) # Only 100 permutations to reduce computation time, but it is recommended to perform at least 1000 permutations
mra <- msviper(sig, regulon, dnull)
plot(mra, cex=.7)
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")'.
Thu Dec 3 02:27:25 2020
Computing the null model distribution by 100 permutations.
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Thu Dec 3 02:27:27 2020
Computing regulon enrichment with aREA algorithm
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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 generate a plot for msviper results showing the enrichment of the target genes for each significant master regulator on the gene expression signature
Usage
1 2 3 4 5 |
Arguments
x |
msviper object produced by |
mrs |
Either an integer indicating the number of master regulators to include in the plot, or a character vector containing the names of the master regulators to include in the plot |
color |
Vector of two components indicating the colors for the negative and positive parts of the regulon |
pval |
Optional matrix of p-values to include in the plot |
bins |
Number of bins to split the vector of scores in order to compute the density color of the bars |
cex |
Number indicating the text size scaling, 0 indicates automatic scaling |
density |
Integrer indicating the number of steps for the kernel density. Zero for not ploting it |
smooth |
Number indicating the proportion of point for smoothing the density distribution. Zero for not using the smoother |
sep |
Number indicating the separation from figure and text |
hybrid |
Logical, whether the 3-tail approach used for computingthe enrichment should be reflected in the plot |
include |
Vector indicating the information to include as heatmap to the right of the msviper plot: expression and activity |
gama |
Positive number indicating the exponential transformation for the activity and expression color scale |
... |
Given for compatibility to the plot generic function |
Value
Nothing, a plot is generated in the default output device
See Also
Examples
1 2 3 4 5 | data(bcellViper, package="bcellViper")
sig <- rowTtest(dset, "description", c("CB", "CC"), "N")$statistic
dnull <- ttestNull(dset, "description", c("CB", "CC"), "N", per=100) # Only 100 permutations to reduce computation time, but it is recommended to perform at least 1000 permutations
mra <- msviper(sig, regulon, dnull)
plot(mra, cex=.7)
|
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")'.
Thu Dec 3 02:27:25 2020
Computing the null model distribution by 100 permutations.
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Thu Dec 3 02:27:27 2020
Computing regulon enrichment with aREA algorithm
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