Browse code

vignette for new workflow

Tom Sherman authored on 11/07/2018 16:09:37
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-% Generated by roxygen2: do not edit by hand
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-% Please edit documentation in R/calcCoGAPSStat.R
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-\name{calcCoGAPSStat}
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-\alias{calcCoGAPSStat}
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-\title{Calculate Gene Set Statistics}
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-\usage{
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-calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
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-}
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-\arguments{
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-\item{Amean}{A matrix mean values}
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-
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-\item{Asd}{A matrix standard deviations}
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-
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-\item{GStoGenes}{data.frame or list with gene sets}
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-
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-\item{numPerm}{number of permutations for null}
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-}
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-\value{
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-gene set statistics for each column of A
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-}
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-\description{
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-Calculate Gene Set Statistics
23
-}
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-\details{
25
-calculates the gene set statistics for each
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-column of A using a Z-score from the elements of the A matrix,
27
-the input gene set, and permutation tests
28
-}
29
-\examples{
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-data('SimpSim')
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-calcCoGAPSStat(SimpSim.result$Amean, SimpSim.result$Asd, GStoGenes=GSets,
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-numPerm=500)
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-}
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-
Browse code

added back docs; fixed RNG syntax

Tom Sherman authored on 31/05/2018 21:34:33
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+% Generated by roxygen2: do not edit by hand
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+% Please edit documentation in R/calcCoGAPSStat.R
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+\name{calcCoGAPSStat}
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+\alias{calcCoGAPSStat}
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+\title{Calculate Gene Set Statistics}
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+\usage{
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+calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
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+}
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+\arguments{
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+\item{Amean}{A matrix mean values}
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+
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+\item{Asd}{A matrix standard deviations}
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+
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+\item{GStoGenes}{data.frame or list with gene sets}
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+
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+\item{numPerm}{number of permutations for null}
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+}
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+\value{
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+gene set statistics for each column of A
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+}
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+\description{
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+Calculate Gene Set Statistics
23
+}
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+\details{
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+calculates the gene set statistics for each
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+column of A using a Z-score from the elements of the A matrix,
27
+the input gene set, and permutation tests
28
+}
29
+\examples{
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+data('SimpSim')
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+calcCoGAPSStat(SimpSim.result$Amean, SimpSim.result$Asd, GStoGenes=GSets,
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+numPerm=500)
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+}
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+
Browse code

make lintr happy

Tom Sherman authored on 31/05/2018 21:28:52
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-% Generated by roxygen2: do not edit by hand
2
-% Please edit documentation in R/calcCoGAPSStat.R
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-\name{calcCoGAPSStat}
4
-\alias{calcCoGAPSStat}
5
-\title{Calculate Gene Set Statistics}
6
-\usage{
7
-calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
8
-}
9
-\arguments{
10
-\item{Amean}{A matrix mean values}
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-
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-\item{Asd}{A matrix standard deviations}
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-
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-\item{GStoGenes}{data.frame or list with gene sets}
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-
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-\item{numPerm}{number of permutations for null}
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-}
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-\value{
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-gene set statistics for each column of A
20
-}
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-\description{
22
-Calculate Gene Set Statistics
23
-}
24
-\details{
25
-calculates the gene set statistics for each
26
-column of A using a Z-score from the elements of the A matrix,
27
-the input gene set, and permutation tests
28
-}
29
-\examples{
30
-data('SimpSim')
31
-calcCoGAPSStat(SimpSim.result$Amean, SimpSim.result$Asd, GStoGenes=GSets,
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-numPerm=500)
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-}
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-
Browse code

more framework

sherman5 authored on 14/02/2018 18:44:00
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@@ -26,4 +26,9 @@ calculates the gene set statistics for each
26 26
 column of A using a Z-score from the elements of the A matrix,
27 27
 the input gene set, and permutation tests
28 28
 }
29
+\examples{
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+data('SimpSim')
31
+calcCoGAPSStat(SimpSim.result$Amean, SimpSim.result$Asd, GStoGenes=GSets,
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+numPerm=500)
33
+}
29 34
 
Browse code

passing BioC checks - removed exported function without working examples

sherman5 authored on 29/01/2018 16:21:13
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@@ -26,11 +26,4 @@ calculates the gene set statistics for each
26 26
 column of A using a Z-score from the elements of the A matrix,
27 27
 the input gene set, and permutation tests
28 28
 }
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-\examples{
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-# Load the sample data from CoGAPS
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-data(SimpSim)
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-# Run calcCoGAPSStat with the correct arguments from 'results'
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-calcCoGAPSStat(SimpSim.result$Amean, SimpSim.result$Asd,
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-GStoGenes=GSets, numPerm=500)
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-}
36 29
 
Browse code

more warning clean up

sherman5 authored on 26/01/2018 20:18:09
Showing1 changed files
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@@ -15,20 +15,22 @@ calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
15 15
 
16 16
 \item{numPerm}{number of permutations for null}
17 17
 }
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+\value{
19
+gene set statistics for each column of A
20
+}
18 21
 \description{
19 22
 Calculate Gene Set Statistics
20 23
 }
21 24
 \details{
22 25
 calculates the gene set statistics for each
23
- column of A using a Z-score from the elements of the A matrix,
24
- the input gene set, and permutation tests
26
+column of A using a Z-score from the elements of the A matrix,
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+the input gene set, and permutation tests
25 28
 }
26 29
 \examples{
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-# Load the simulated data
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-data('SimpSim')
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-# Load the outputs from gapsRun
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-data('results')
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+# Load the sample data from CoGAPS
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+data(SimpSim)
31 32
 # Run calcCoGAPSStat with the correct arguments from 'results'
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-calcCoGAPSStat(results$Amean,results$Asd,GStoGenes=GSets,numPerm=500)
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+calcCoGAPSStat(SimpSim.result$Amean, SimpSim.result$Asd,
34
+GStoGenes=GSets, numPerm=500)
33 35
 }
34 36
 
sherman5 authored on 26/01/2018 17:53:51
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Browse code

cleaning up notes for v3

sherman5 authored on 24/01/2018 23:38:02
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@@ -2,9 +2,7 @@
2 2
 % Please edit documentation in R/calcCoGAPSStat.R
3 3
 \name{calcCoGAPSStat}
4 4
 \alias{calcCoGAPSStat}
5
-\title{\code{calcCoGAPSStat} calculates the gene set statistics for each
6
-column of A using a Z-score from the elements of the A matrix,
7
-the input gene set, and permutation tests}
5
+\title{Calculate Gene Set Statistics}
8 6
 \usage{
9 7
 calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
10 8
 }
... ...
@@ -18,8 +16,11 @@ calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
18 16
 \item{numPerm}{number of permutations for null}
19 17
 }
20 18
 \description{
21
-\code{calcCoGAPSStat} calculates the gene set statistics for each
22
-column of A using a Z-score from the elements of the A matrix,
23
-the input gene set, and permutation tests
19
+Calculate Gene Set Statistics
20
+}
21
+\details{
22
+calculates the gene set statistics for each
23
+ column of A using a Z-score from the elements of the A matrix,
24
+ the input gene set, and permutation tests
24 25
 }
25 26
 
Browse code

New examples

Maggie Wodicka authored on 24/01/2018 16:02:01
Showing1 changed files
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@@ -22,4 +22,11 @@ calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
22 22
 column of A using a Z-score from the elements of the A matrix,
23 23
 the input gene set, and permutation tests
24 24
 }
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-
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+\examples{
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+# Load the simulated data
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+data('SimpSim')
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+# Load the outputs from gapsRun
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+data('results')
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+# Run calcCoGAPSStat with the correct arguments from 'results'
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+calcCoGAPSStat(results$Amean,results$Asd,GStoGenes=GSets,numPerm=500)
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+}
Browse code

added C++ unit tests

sherman5 authored on 06/09/2017 19:58:09
Showing1 changed files
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@@ -22,3 +22,4 @@ calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
22 22
 column of A using a Z-score from the elements of the A matrix,
23 23
 the input gene set, and permutation tests
24 24
 }
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+
Tom Sherman authored on 18/04/2017 18:38:46
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@@ -22,4 +22,3 @@ calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
22 22
 column of A using a Z-score from the elements of the A matrix,
23 23
 the input gene set, and permutation tests
24 24
 }
25
-
Browse code

Run `document`

Jacob Carey authored on 18/12/2015 21:07:44
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@@ -1,36 +1,25 @@
1
+% Generated by roxygen2: do not edit by hand
2
+% Please edit documentation in R/calcCoGAPSStat.R
1 3
 \name{calcCoGAPSStat}
2 4
 \alias{calcCoGAPSStat}
3
-\title{CoGAPS gene set statistic}
4
-
5
-\description{
6
-Computes the p-value for the association of underlying patterns from microarray data to activity in gene sets.}
7
-
5
+\title{\code{calcCoGAPSStat} calculates the gene set statistics for each
6
+column of A using a Z-score from the elements of the A matrix,
7
+the input gene set, and permutation tests}
8 8
 \usage{
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-  calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm=500)}
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-
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-\arguments{
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-\item{Amean}{Sampled mean value of the amplitude matrix \eqn{{{A}}}.  \code{row.names(Amean)} must correspond to the gene names contained in GStoGenes.}
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-\item{Asd}{Sampled standard deviation of the amplitude matrix \eqn{{{A}}}.}
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-\item{GStoGenes}{List or data frame containing the genes in each gene set. If a list, gene set names are the list names and corresponding elements are the names of genes contained in each set. If a data frame, gene set names are in the first column and corresponding gene names are listed in rows beneath each gene set name.}
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-\item{numPerm}{Number of permuations used for the null distribution in the gene set statistic. (optional; default=500)}
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-}
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-
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-\details{
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-  This script links the patterns identified in the columns of \eqn{{P}}  to activity in each of the gene sets specified in GStoGenes using a novel z-score based statistic developed in Ochs et al. (2009).  Specifically, the z-score for pattern \eqn{p} and gene set \eqn{G_{i}} containing \eqn{G} total genes is given by \deqn{Z_{i,p} = \frac{1}{G} \sum_{g in G_{i}}A_{gp} / \sigma_{gp}}, where \eqn{g} indexes the genes in the set and \eqn{\sigma_{gp}} is the standard deviation of \eqn{{{A}}_{gp}} obtained from MCMC sampling.  CoGAPS then uses the specified \code{numPerm} random sample tests to compute a consistent p value estimate from that z score.
9
+calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm = 500)
20 10
 }
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+\arguments{
12
+\item{Amean}{A matrix mean values}
21 13
 
22
-\value{
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-  A list containing:
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-  \item{GSUpreg}{p-values for upregulation of each gene set in each pattern.}
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-  \item{GSDownreg}{p-values for downregulation of each gene set in each pattern.}
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-  \item{GSActEst}{p-values for activity of each gene set in each pattern.}
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-}
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+\item{Asd}{A matrix standard deviations}
28 15
 
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-\author{Elana J. Fertig \email{ejfertig@jhmi.edu}}
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+\item{GStoGenes}{data.frame or list with gene sets}
30 17
 
31
-\references{
32
-M.F. Ochs, L. Rink, C. Tarn, S. Mburu, T. Taguchi, B. Eisenberg, and A.K. Godwin.  (2009) Detection and treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic data.  Cancer Research, 69:9125-9132.
18
+\item{numPerm}{number of permutations for null}
19
+}
20
+\description{
21
+\code{calcCoGAPSStat} calculates the gene set statistics for each
22
+column of A using a Z-score from the elements of the A matrix,
23
+the input gene set, and permutation tests
33 24
 }
34 25
 
35
-\seealso{\code{\link{CoGAPS}}}
36
-\keyword{misc}
Browse code

New working version with boost in place of JAGS

git-svn-id: https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/CoGAPS@94364 bc3139a8-67e5-0310-9ffc-ced21a209358

e.fertig authored on 22/09/2014 17:32:24
Showing1 changed files
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@@ -32,5 +32,5 @@ Computes the p-value for the association of underlying patterns from microarray
32 32
 M.F. Ochs, L. Rink, C. Tarn, S. Mburu, T. Taguchi, B. Eisenberg, and A.K. Godwin.  (2009) Detection and treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic data.  Cancer Research, 69:9125-9132.
33 33
 }
34 34
 
35
-\seealso{\code{\link{CoGAPS}}, \code{\link{GAPS}}}
35
+\seealso{\code{\link{CoGAPS}}}
36 36
 \keyword{misc}
Browse code

Included description of statistics in .Rd files

git-svn-id: https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/CoGAPS@68161 bc3139a8-67e5-0310-9ffc-ced21a209358

e.fertig authored on 02/08/2012 18:25:56
Showing1 changed files
... ...
@@ -9,14 +9,14 @@ Computes the p-value for the association of underlying patterns from microarray
9 9
   calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm=500)}
10 10
 
11 11
 \arguments{
12
-\item{Amean}{Sampled mean value of the amplitude matrix \eqn{{\bf{A}}}.  \code{row.names(Amean)} must correspond to the gene names contained in GStoGenes.}
13
-\item{Asd}{Sampled standard deviation of the amplitude matrix \eqn{{\bf{A}}}.}
12
+\item{Amean}{Sampled mean value of the amplitude matrix \eqn{{{A}}}.  \code{row.names(Amean)} must correspond to the gene names contained in GStoGenes.}
13
+\item{Asd}{Sampled standard deviation of the amplitude matrix \eqn{{{A}}}.}
14 14
 \item{GStoGenes}{List or data frame containing the genes in each gene set. If a list, gene set names are the list names and corresponding elements are the names of genes contained in each set. If a data frame, gene set names are in the first column and corresponding gene names are listed in rows beneath each gene set name.}
15 15
 \item{numPerm}{Number of permuations used for the null distribution in the gene set statistic. (optional; default=500)}
16 16
 }
17 17
 
18 18
 \details{
19
-  This script links the patterns identified in the columns of \eqn{\bf{P}}  to activity in each of the gene sets specified in GStoGenes using a novel z-score based statistic developed in Ochs et al. (2009).  Specifically, the z-score for pattern \eqn{p} and gene set \eqn{G_{i}} containing $G$ total genes is given by \deqn{Z_{i,p} = \frac{1}{G} \sum_{g in \mathcal{G_{i}}} {\frac{{\bf{A}_{gp}}}{\sigma_{gp}}},} where \eqn{g} indexes the genes in the set and \eqn{\sigma_{gp}} is the standard deviation of \eqn{{\bf{A}}_{gp}} obtained from MCMC sampling.  CoGAPS then uses the specified \code{numPerm} random sample tests to compute a consistent p value estimate from that z score.
19
+  This script links the patterns identified in the columns of \eqn{{P}}  to activity in each of the gene sets specified in GStoGenes using a novel z-score based statistic developed in Ochs et al. (2009).  Specifically, the z-score for pattern \eqn{p} and gene set \eqn{G_{i}} containing \eqn{G} total genes is given by \deqn{Z_{i,p} = \frac{1}{G} \sum_{g in G_{i}}A_{gp} / \sigma_{gp}}, where \eqn{g} indexes the genes in the set and \eqn{\sigma_{gp}} is the standard deviation of \eqn{{{A}}_{gp}} obtained from MCMC sampling.  CoGAPS then uses the specified \code{numPerm} random sample tests to compute a consistent p value estimate from that z score.
20 20
 }
21 21
 
22 22
 \value{
Browse code

Added the CoGAPS package.

git-svn-id: https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/CoGAPS@48067 bc3139a8-67e5-0310-9ffc-ced21a209358

c.wong authored on 12/07/2010 17:26:34
Showing1 changed files
1 1
new file mode 100644
... ...
@@ -0,0 +1,36 @@
1
+\name{calcCoGAPSStat}
2
+\alias{calcCoGAPSStat}
3
+\title{CoGAPS gene set statistic}
4
+
5
+\description{
6
+Computes the p-value for the association of underlying patterns from microarray data to activity in gene sets.}
7
+
8
+\usage{
9
+  calcCoGAPSStat(Amean, Asd, GStoGenes, numPerm=500)}
10
+
11
+\arguments{
12
+\item{Amean}{Sampled mean value of the amplitude matrix \eqn{{\bf{A}}}.  \code{row.names(Amean)} must correspond to the gene names contained in GStoGenes.}
13
+\item{Asd}{Sampled standard deviation of the amplitude matrix \eqn{{\bf{A}}}.}
14
+\item{GStoGenes}{List or data frame containing the genes in each gene set. If a list, gene set names are the list names and corresponding elements are the names of genes contained in each set. If a data frame, gene set names are in the first column and corresponding gene names are listed in rows beneath each gene set name.}
15
+\item{numPerm}{Number of permuations used for the null distribution in the gene set statistic. (optional; default=500)}
16
+}
17
+
18
+\details{
19
+  This script links the patterns identified in the columns of \eqn{\bf{P}}  to activity in each of the gene sets specified in GStoGenes using a novel z-score based statistic developed in Ochs et al. (2009).  Specifically, the z-score for pattern \eqn{p} and gene set \eqn{G_{i}} containing $G$ total genes is given by \deqn{Z_{i,p} = \frac{1}{G} \sum_{g in \mathcal{G_{i}}} {\frac{{\bf{A}_{gp}}}{\sigma_{gp}}},} where \eqn{g} indexes the genes in the set and \eqn{\sigma_{gp}} is the standard deviation of \eqn{{\bf{A}}_{gp}} obtained from MCMC sampling.  CoGAPS then uses the specified \code{numPerm} random sample tests to compute a consistent p value estimate from that z score.
20
+}
21
+
22
+\value{
23
+  A list containing:
24
+  \item{GSUpreg}{p-values for upregulation of each gene set in each pattern.}
25
+  \item{GSDownreg}{p-values for downregulation of each gene set in each pattern.}
26
+  \item{GSActEst}{p-values for activity of each gene set in each pattern.}
27
+}
28
+
29
+\author{Elana J. Fertig \email{ejfertig@jhmi.edu}}
30
+
31
+\references{
32
+M.F. Ochs, L. Rink, C. Tarn, S. Mburu, T. Taguchi, B. Eisenberg, and A.K. Godwin.  (2009) Detection and treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic data.  Cancer Research, 69:9125-9132.
33
+}
34
+
35
+\seealso{\code{\link{CoGAPS}}, \code{\link{GAPS}}}
36
+\keyword{misc}