q-order partial correlation graphs, or qp-graphs for short, are undirected Gaussian graphical Markov models built from q-order partial correlations. They are useful for learning undirected graphical Gaussian Markov models from data sets where the number of random variables p exceeds the available sample size n as, for instance, in the case of microarray data where they can be employed to reverse engineer a molecular regulatory network.
| Author | R. Castelo and A. Roverato |
| Maintainer | Robert Castelo |
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("qpgraph")
| Reverse-engineer transcriptional regulatory networks using qpgraph | R Script | |
|---|---|---|
| qpPCCdistbyTF.pdf | ||
| qpPreRecComparison.pdf | ||
| qpPreRecComparisonFullRecall.pdf | ||
| qpTRnet50pctpre.pdf | ||
| Reference Manual |
| biocViews | |
|---|---|
| Depends |
methods
,
Biobase
,
AnnotationDbi
|
| Imports |
methods
,
Biobase
,
AnnotationDbi
|
| Suggests | |
| System Requirements | |
| License | GPL (>= 2) |
| URL | http://functionalgenomics.upf.edu/qpgraph |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
| Package source | qpgraph_1.4.1.tar.gz |
|---|---|
| Windows 32-bit binary | qpgraph_1.4.1.zip |
| Windows 64-bit binary | qpgraph_1.4.1.zip |
| MacOS X 10.5 (Leopard) binary | qpgraph_1.4.1.tgz |
| Package Downloads Report | Downloads Stats |