1. NetPathMiner
  2. man
  3. samplePaths.Rd
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Docs update 1.19

Ahmed Mohamed authored on 01/03/2019 06:31:42
Showing1 changed files
man/samplePaths.Rd
History View file @087265c
... ... 
@@ -4,8 +4,8 @@
4 4 
 \alias{samplePaths}
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 \title{Creates a set of sample path p-values for each length given a weighted network}
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 \usage{
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-samplePaths(graph, max.path.length, num.samples = 1000, num.warmup = 10,
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-  verbose = TRUE)
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+samplePaths(graph, max.path.length, num.samples = 1000,
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+  num.warmup = 10, verbose = TRUE)
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 }
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 \arguments{
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 \item{graph}{A weighted igraph object. Weights must be in \code{edge.weights} or \code{weight}
... ... 
@@ -23,7 +23,7 @@ edge attributes.}
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 A matrix where each row is a path length and each column is the number of paths sampled.
24 24 
 }
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 \description{
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-Randomly traverses paths of increasing lengths within a set network to create an
26 
+Randomly traverses paths of increasing lengths within a set network to create an
27 27 
 empirical pathway distribution for more accurate determination of path significance.
28 28 
 }
29 29 
 \details{
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@@ -39,26 +39,26 @@ Can take a bit of time.
39 39 
  # Calculate Pearson's correlation.
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 	data(ex_microarray)	# Part of ALL dataset.
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 	rgraph <- assignEdgeWeights(microarray = ex_microarray, graph = rgraph,
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-		weight.method = "cor", use.attr="miriam.uniprot",
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+		weight.method = "cor", use.attr="miriam.uniprot",
43 43 
 		y=factor(colnames(ex_microarray)), bootstrap = FALSE)
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-
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+
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 	## Get significantly correlated paths using "p-valvue" method.
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-	##   First, establish path score distribution by calling "samplePaths"
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+	##   First, establish path score distribution by calling "samplePaths"
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  pathsample <- samplePaths(rgraph, max.path.length=10,
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                         num.samples=100, num.warmup=10)
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-
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-	##   Get all significant paths with p<0.1
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-	significant.p <- pathRanker(rgraph, method = "pvalue",
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+
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+	##   Get all significant paths with p<0.1
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+	significant.p <- pathRanker(rgraph, method = "pvalue",
52 52 
                 sampledpaths = pathsample ,alpha=0.1)
53 53
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-}
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-\author{
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-Timothy Hancock
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-
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-Ahmed Mohamed
59 54 
 }
60 55 
 \seealso{
61 56 
 Other Path ranking methods: \code{\link{extractPathNetwork}},
62 57 
   \code{\link{getPathsAsEIDs}}, \code{\link{pathRanker}}
63 58 
 }
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+\author{
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+Timothy Hancock
64 61
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+Ahmed Mohamed
63 
+}
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+\concept{Path ranking methods}
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update docs using roxygen2

ahmohamed authored on 19/09/2016 02:16:33
Showing1 changed files
man/samplePaths.Rd
History View file @2aadfaf
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@@ -1,4 +1,5 @@
1 
-% Generated by roxygen2 (4.0.1): do not edit by hand
1 
+% Generated by roxygen2: do not edit by hand
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+% Please edit documentation in R/pathRank.R
2 3 
 \name{samplePaths}
3 4 
 \alias{samplePaths}
4 5 
 \title{Creates a set of sample path p-values for each length given a weighted network}
... ... 
@@ -22,14 +23,14 @@ edge attributes.}
22 23 
 A matrix where each row is a path length and each column is the number of paths sampled.
23 24 
 }
24 25 
 \description{
25 
-Randomly traverses paths of increasing lengths within a set network to create an
26 
+Randomly traverses paths of increasing lengths within a set network to create an
26 27 
 empirical pathway distribution for more accurate determination of path significance.
27 28 
 }
28 29 
 \details{
29 30 
 Can take a bit of time.
30 31 
 }
31 32 
 \examples{
32 
-## Prepare a weighted reaction network.
33 
+	## Prepare a weighted reaction network.
33 34 
 	## Conver a metabolic network to a reaction network.
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  data(ex_sbml) # bipartite metabolic network of Carbohydrate metabolism.
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  rgraph <- makeReactionNetwork(ex_sbml, simplify=TRUE)
... ... 
@@ -38,17 +39,18 @@ Can take a bit of time.
38 39 
  # Calculate Pearson's correlation.
39 40 
 	data(ex_microarray)	# Part of ALL dataset.
40 41 
 	rgraph <- assignEdgeWeights(microarray = ex_microarray, graph = rgraph,
41 
-		weight.method = "cor", use.attr="miriam.uniprot",
42 
+		weight.method = "cor", use.attr="miriam.uniprot",
42 43 
 		y=factor(colnames(ex_microarray)), bootstrap = FALSE)
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-
44 
+
44 45 
 	## Get significantly correlated paths using "p-valvue" method.
45 
-	##   First, establish path score distribution by calling "samplePaths"
46 
+	##   First, establish path score distribution by calling "samplePaths"
46 47 
  pathsample <- samplePaths(rgraph, max.path.length=10,
47 48 
                         num.samples=100, num.warmup=10)
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-
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-	##   Get all significant paths with p<0.1
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-	significant.p <- pathRanker(rgraph, method = "pvalue",
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+
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+	##   Get all significant paths with p<0.1
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+	significant.p <- pathRanker(rgraph, method = "pvalue",
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                 sampledpaths = pathsample ,alpha=0.1)
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+
52 54 
 }
53 55 
 \author{
54 56 
 Timothy Hancock
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@@ -56,7 +58,7 @@ Timothy Hancock
56 58 
 Ahmed Mohamed
57 59 
 }
58 60 
 \seealso{
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-Other Path ranking methods: \code{\link{extractPathNetwork}};
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-  \code{\link{getPathsAsEIDs}}; \code{\link{pathRanker}}
61 
+Other Path ranking methods: \code{\link{extractPathNetwork}},
62 
+  \code{\link{getPathsAsEIDs}}, \code{\link{pathRanker}}
61 63 
 }
62 64
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empty commit

Ahmed Mohamed authored on 04/07/2015 00:36:26
Showing1 changed files
man/samplePaths.Rd
History View file @555ec75
1 1 
old mode 100644
2 2 
new mode 100755
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Updates

added plotCytoscapeGML , Geneset export formats, bug fixes

amfy10 authored on 28/06/2014 15:36:04
Showing1 changed files
man/samplePaths.Rd
History View file @a6b3c97
... ... 
@@ -1,3 +1,4 @@
1 
+% Generated by roxygen2 (4.0.1): do not edit by hand
1 2 
 \name{samplePaths}
2 3 
 \alias{samplePaths}
3 4 
 \title{Creates a set of sample path p-values for each length given a weighted network}
... ... 
@@ -6,26 +7,23 @@ samplePaths(graph, max.path.length, num.samples = 1000, num.warmup = 10,
6 7 
   verbose = TRUE)
7 8 
 }
8 9 
 \arguments{
9 
-  \item{graph}{A weighted igraph object. Weights must be in
10 
-  \code{edge.weights} or \code{weight} edge attributes.}
10 
+\item{graph}{A weighted igraph object. Weights must be in \code{edge.weights} or \code{weight}
11 
+edge attributes.}
11 12
12 
-  \item{max.path.length}{The maxmimum path length.}
13 
+\item{max.path.length}{The maxmimum path length.}
13 14
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-  \item{num.samples}{The numner of paths to sample}
15 
+\item{num.samples}{The numner of paths to sample}
15 16
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-  \item{num.warmup}{The number of warm up paths to sample.}
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+\item{num.warmup}{The number of warm up paths to sample.}
17 18
18 
-  \item{verbose}{Whether to display the progress of the
19 
-  function.}
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+\item{verbose}{Whether to display the progress of the function.}
20 20 
 }
21 21 
 \value{
22 
-A matrix where each row is a path length and each column is
23 
-the number of paths sampled.
22 
+A matrix where each row is a path length and each column is the number of paths sampled.
24 23 
 }
25 24 
 \description{
26 
-Randomly traverses paths of increasing lengths within a set
27 
-network to create an empirical pathway distribution for
28 
-more accurate determination of path significance.
25 
+Randomly traverses paths of increasing lengths within a set network to create an
26 
+empirical pathway distribution for more accurate determination of path significance.
29 27 
 }
30 28 
 \details{
31 29 
 Can take a bit of time.
... ... 
@@ -58,8 +56,7 @@ Timothy Hancock
58 56 
 Ahmed Mohamed
59 57 
 }
60 58 
 \seealso{
61 
-Other Path ranking methods:
62 
-\code{\link{extractPathNetwork}};
63 
-\code{\link{getPathsAsEIDs}}; \code{\link{pathRanker}}
59 
+Other Path ranking methods: \code{\link{extractPathNetwork}};
60 
+  \code{\link{getPathsAsEIDs}}; \code{\link{pathRanker}}
64 61 
 }
65 62
Browse code

Release 0.99.0 Biocunductor submission

amfy10 authored on 10/03/2014 12:16:44
Showing1 changed files
man/samplePaths.Rd
History View file @96e22bf
1 1 
new file mode 100644
... ... 
@@ -0,0 +1,65 @@
1 
+\name{samplePaths}
2 
+\alias{samplePaths}
3 
+\title{Creates a set of sample path p-values for each length given a weighted network}
4 
+\usage{
5 
+samplePaths(graph, max.path.length, num.samples = 1000, num.warmup = 10,
6 
+  verbose = TRUE)
7 
+}
8 
+\arguments{
9 
+  \item{graph}{A weighted igraph object. Weights must be in
10 
+  \code{edge.weights} or \code{weight} edge attributes.}
11 
+
12 
+  \item{max.path.length}{The maxmimum path length.}
13 
+
14 
+  \item{num.samples}{The numner of paths to sample}
15 
+
16 
+  \item{num.warmup}{The number of warm up paths to sample.}
17 
+
18 
+  \item{verbose}{Whether to display the progress of the
19 
+  function.}
20 
+}
21 
+\value{
22 
+A matrix where each row is a path length and each column is
23 
+the number of paths sampled.
24 
+}
25 
+\description{
26 
+Randomly traverses paths of increasing lengths within a set
27 
+network to create an empirical pathway distribution for
28 
+more accurate determination of path significance.
29 
+}
30 
+\details{
31 
+Can take a bit of time.
32 
+}
33 
+\examples{
34 
+## Prepare a weighted reaction network.
35 
+	## Conver a metabolic network to a reaction network.
36 
+ data(ex_sbml) # bipartite metabolic network of Carbohydrate metabolism.
37 
+ rgraph <- makeReactionNetwork(ex_sbml, simplify=TRUE)
38 
+
39 
+	## Assign edge weights based on Affymetrix attributes and microarray dataset.
40 
+ # Calculate Pearson's correlation.
41 
+	data(ex_microarray)	# Part of ALL dataset.
42 
+	rgraph <- assignEdgeWeights(microarray = ex_microarray, graph = rgraph,
43 
+		weight.method = "cor", use.attr="miriam.uniprot",
44 
+		y=factor(colnames(ex_microarray)), bootstrap = FALSE)
45 
+
46 
+	## Get significantly correlated paths using "p-valvue" method.
47 
+	##   First, establish path score distribution by calling "samplePaths"
48 
+ pathsample <- samplePaths(rgraph, max.path.length=10,
49 
+                        num.samples=100, num.warmup=10)
50 
+
51 
+	##   Get all significant paths with p<0.1
52 
+	significant.p <- pathRanker(rgraph, method = "pvalue",
53 
+                sampledpaths = pathsample ,alpha=0.1)
54 
+}
55 
+\author{
56 
+Timothy Hancock
57 
+
58 
+Ahmed Mohamed
59 
+}
60 
+\seealso{
61 
+Other Path ranking methods:
62 
+\code{\link{extractPathNetwork}};
63 
+\code{\link{getPathsAsEIDs}}; \code{\link{pathRanker}}
64 
+}
65 
+