Browse code

Docs update 1.19

Ahmed Mohamed authored on 01/03/2019 06:31:42
Showing1 changed files
... ...
@@ -4,8 +4,8 @@
4 4
 \alias{samplePaths}
5 5
 \title{Creates a set of sample path p-values for each length given a weighted network}
6 6
 \usage{
7
-samplePaths(graph, max.path.length, num.samples = 1000, num.warmup = 10,
8
-  verbose = TRUE)
7
+samplePaths(graph, max.path.length, num.samples = 1000,
8
+  num.warmup = 10, verbose = TRUE)
9 9
 }
10 10
 \arguments{
11 11
 \item{graph}{A weighted igraph object. Weights must be in \code{edge.weights} or \code{weight}
... ...
@@ -23,7 +23,7 @@ edge attributes.}
23 23
 A matrix where each row is a path length and each column is the number of paths sampled.
24 24
 }
25 25
 \description{
26
-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{
... ...
@@ -39,26 +39,26 @@ Can take a bit of time.
39 39
  # Calculate Pearson's correlation.
40 40
 	data(ex_microarray)	# Part of ALL dataset.
41 41
 	rgraph <- assignEdgeWeights(microarray = ex_microarray, graph = rgraph,
42
-		weight.method = "cor", use.attr="miriam.uniprot", 
42
+		weight.method = "cor", use.attr="miriam.uniprot",
43 43
 		y=factor(colnames(ex_microarray)), bootstrap = FALSE)
44
- 
44
+
45 45
 	## Get significantly correlated paths using "p-valvue" method.
46
-	##   First, establish path score distribution by calling "samplePaths" 
46
+	##   First, establish path score distribution by calling "samplePaths"
47 47
  pathsample <- samplePaths(rgraph, max.path.length=10,
48 48
                         num.samples=100, num.warmup=10)
49
-	
50
-	##   Get all significant paths with p<0.1 
51
-	significant.p <- pathRanker(rgraph, method = "pvalue", 
49
+
50
+	##   Get all significant paths with p<0.1
51
+	significant.p <- pathRanker(rgraph, method = "pvalue",
52 52
                 sampledpaths = pathsample ,alpha=0.1)
53 53
 
54
-}
55
-\author{
56
-Timothy Hancock
57
-
58
-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
 }
59
+\author{
60
+Timothy Hancock
64 61
 
62
+Ahmed Mohamed
63
+}
64
+\concept{Path ranking methods}
Browse code

update docs using roxygen2

ahmohamed authored on 19/09/2016 02:16:33
Showing1 changed files
... ...
@@ -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
2
+% 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.
34 35
  data(ex_sbml) # bipartite metabolic network of Carbohydrate metabolism.
35 36
  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)
43
-
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)
48
-
49
-	##   Get all significant paths with p<0.1
50
-	significant.p <- pathRanker(rgraph, method = "pvalue",
49
+	
50
+	##   Get all significant paths with p<0.1 
51
+	significant.p <- pathRanker(rgraph, method = "pvalue", 
51 52
                 sampledpaths = pathsample ,alpha=0.1)
53
+
52 54
 }
53 55
 \author{
54 56
 Timothy Hancock
... ...
@@ -56,7 +58,7 @@ Timothy Hancock
56 58
 Ahmed Mohamed
57 59
 }
58 60
 \seealso{
59
-Other Path ranking methods: \code{\link{extractPathNetwork}};
60
-  \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
 
Browse code

empty commit

Ahmed Mohamed authored on 04/07/2015 00:36:26
Showing1 changed files
1 1
old mode 100644
2 2
new mode 100755
Browse code

Updates

added plotCytoscapeGML , Geneset export formats, bug fixes

amfy10 authored on 28/06/2014 15:36:04
Showing1 changed files
... ...
@@ -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
 
14
-  \item{num.samples}{The numner of paths to sample}
15
+\item{num.samples}{The numner of paths to sample}
15 16
 
16
-  \item{num.warmup}{The number of warm up paths to sample.}
17
+\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.}
19
+\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
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
+