version 0.6-4

DESCRIPTION

@@ -1,18 +1,19 @@
 Package: polySegratioMM
 Type: Package
-Title: Bayesian mixture models for marker dosage in autopolyploids
-Version: 0.6-3
-Date: 2014-02-06
-Author: Peter Baker
+Title: Bayesian Mixture Models for Marker Dosage in Autopolyploids
+Version: 0.6-4
+Date: 2018-03-22
+Authors@R: c(person("Peter", "Baker", role = c("aut", "cre"),
+                       email = "p.baker1@uq.edu.au"))
+Author: Peter Baker [aut, cre]
 Maintainer: Peter Baker <p.baker1@uq.edu.au>
 Depends: R (>= 2.12.0), polySegratio
 Imports: gtools, coda, lattice
-Description: Fits Bayesian mixture models to estimate marker dosage for dominant markers on autopolyploids using JAGS (1.0 or greater) as outlined in Baker et al (2010). May be used in conjunction with polySegratio for simulation studies and comparison with standard methods.
+Description: Fits Bayesian mixture models to estimate marker dosage for dominant markers in autopolyploids using JAGS (1.0 or greater) as outlined in Baker et al "Bayesian estimation of marker dosage in sugarcane and other autopolyploids" (2010, <doi:10.1007/s00122-010-1283-z>). May be used in conjunction with polySegratio for simulation studies and comparison with standard methods.
+URL: https://github.com/petebaker/polysegratiomm
+BugReports: https://github.com/petebaker/polysegratiomm/issues
 License: GPL-3
-Repository: CRAN
-Repository/R-Forge/Project: polysegratio
-Repository/R-Forge/Revision: 13
-Repository/R-Forge/DateTimeStamp: 2014-03-06 07:37:23
-Date/Publication: 2014-03-06 22:09:58
-Packaged: 2014-03-06 11:36:44 UTC; rforge
 NeedsCompilation: no
+Packaged: 2018-03-23 05:04:53 UTC; pete
+Repository: CRAN
+Date/Publication: 2018-03-23 08:49:42 UTC

MD5

@@ -1,6 +1,6 @@
 da2e46f447c23d885026c21b6b0afa2d *CHANGELOG
-9ced09bc268d7f05566127d345ad1015 *DESCRIPTION
-23a714bc9dd3124183c408ced9caa2f1 *NAMESPACE
+bfd913a98c58f4b09755d6900ee72f7f *DESCRIPTION
+313c26ba2bf3470b49001c2278cd32ff *NAMESPACE
 ff86e117bf0b39f4c0f38dcb8cd80e8f *R/DistributionPlotBinomial.R
 de57e9f029ac5944d7934a752394ddee *R/DistributionPlotGamma.R
 799cab60974371b6eebc988a25b1c209 *R/DistributionPlotNorm.R
@@ -12,7 +12,7 @@ e09ad91c311f78cf2a0f1690d2771e2c *R/dumpInits.R
 b8ed6689c899a189802caba27c6be793 *R/plot.runJagsWrapper.R
 2de6f66f125e251ca251aa39aeeaba40 *R/plot.segratioMCMC.R
 5316489dea5451945be054e1970a85eb *R/plotFitted.R
-96ff69426087132bc47151a2c41bb692 *R/plotTheoretical.R
+c0866e90195b2809d8ce727a87cc2eb0 *R/plotTheoretical.R
 9ce55679aff0f54f5e6a5e378c7660f0 *R/print.dosagesMCMC.R
 f362e9abd45438023fae8ba8d7c51000 *R/print.runJags.R
 bbf017771e438b4bbe7c42374c51d9f1 *R/print.runJagsWrapper.R
@@ -27,15 +27,16 @@ f27c93c3b0802f76fa05dd6dd7394d26 *R/runJags.R
 969e777bbbc8c7e79164d0ffb605c003 *R/summary.segratioMCMC.R
 8ddc61f60708990ecf02bebe9f3edab9 *R/writeControlFile.R
 04ab554ec6e44db7bddcec221160cfee *R/writeJagsFile.R
+906430effa3faa9d85375ba0a6a7115d *README.md
 3d312f9e07e20e3d27cab8b95092855b *TODO
-d7f817d68b921aea959a0cd7a814e99f *build/vignette.rds
+5c9b8cc08d2c2eec6826841dade9d593 *build/vignette.rds
 e3851875d8153cc6b9e49f6cca299109 *data/hexmarkers.RData
 534c6829022b3be2f7005072355fadf8 *data/hexmarkers.overdisp.RData
 1fb84bbf8ea4c37fc03f8d4b0e14bda0 *data/mcmcHexRun.RData
-08b5df5bc5effb0d9cd5141adf02530d *inst/CITATION
-10187c811a16f2892f9e2ecf4f5cd387 *inst/doc/polySegratioMM-overview.R
-6c985ad192ef784993e17c4f9b3b35b8 *inst/doc/polySegratioMM-overview.Rnw
-b7fd91824bcea52b26baee5f8a1a8bce *inst/doc/polySegratioMM-overview.pdf
+46e67cf94e56daee8089d170925ac2eb *inst/CITATION
+db78ca43b17a7ec81105587539ab4879 *inst/doc/polySegratioMM-overview.R
+248bfbb6e2ab3c82938a58d2d808e809 *inst/doc/polySegratioMM-overview.Rnw
+66576a4862d27ac0f10a5a36e8c3a891 *inst/doc/polySegratioMM-overview.pdf
 bea987e891ae6782fe6f1bbead8d0208 *man/DistributionPlotBinomial.Rd
 af9345b52da76bc8db49803e5918a0da *man/calculateDIC.Rd
 e4b8cec052b56995aa4303d5210c2803 *man/diagnosticsJagsMix.Rd
@@ -46,7 +47,7 @@ f93a468ef51f47372fff7fe2d4e6beb5 *man/hexmarkers.Rd
 cfdfc1d615f577ca76aa12433ed9672d *man/mcmcHexRun.Rd
 bb493f0db0e1532c7dedd10372688b5b *man/plot.segratioMCMC.Rd
 2a9c44f0c28f954b7f2f20fa0be675ff *man/plotFitted.Rd
-5ce36bb9fb9dff523bc1fb4a9a6492e3 *man/polySegratioMM-package.Rd
+2ed15f1e9475327e495933a281119c02 *man/polySegratioMM-package.Rd
 571f26e6e8e696e47205d9b0a436387b *man/print.dosagesMCMC.Rd
 2a614f7ddaf297b9cdfe3abbca07587d *man/print.runJags.Rd
 af2fb3e7b9d599cc267cbd921e3d4271 *man/readJags.Rd
@@ -61,13 +62,13 @@ f63d46efa23500dbdcb44435c5792c50 *man/writeControlFile.Rd
 4442c599f34d83f1a0322c26299b0620 *man/writeJagsFile.Rd
 d27a0aa951adedafed99336840ea583a *vignettes/auto/_region_.el
 83fb7c5590475616025be208ee5058ca *vignettes/auto/polySegratioMM-overview.el
-6c985ad192ef784993e17c4f9b3b35b8 *vignettes/polySegratioMM-overview.Rnw
+248bfbb6e2ab3c82938a58d2d808e809 *vignettes/polySegratioMM-overview.Rnw
 839b039e113d02032270bd353e84d955 *vignettes/polySegratioMM-overview.bib
 87d0641c637e5aa1a5f8b3882c49ef02 *vignettes/tmp/tmp-006.eps
-452a2642d967de8446c01698123e69e5 *vignettes/tmp/tmp-006.pdf
+840269e07b335287e6de01c076608e97 *vignettes/tmp/tmp-006.pdf
 169490fb4220165964bd2f1e9421f0fd *vignettes/tmp/tmp-009.eps
-1c71717ebc0b16314c366afcff29cfd0 *vignettes/tmp/tmp-009.pdf
+84ea75418b9869a0ec2f4fb2bab26cf3 *vignettes/tmp/tmp-009.pdf
 482143171f1c518e870b408bb57e2429 *vignettes/tmp/tmp-016.eps
-85b9cab4ee8e66bbf6207247b4b25859 *vignettes/tmp/tmp-016.pdf
+e11219ef0657bb3fc4f76ce8c88907b2 *vignettes/tmp/tmp-016.pdf
 59ff81c4931b659a699ccc0b09aa6522 *vignettes/tmp/tmp-017.eps
-46466ffd0395c73d9eda155d622f3ff4 *vignettes/tmp/tmp-017.pdf
+802ae3438490cf67ce731b93edb4acce *vignettes/tmp/tmp-017.pdf

NAMESPACE

@@ -2,6 +2,7 @@ export(diagnosticsJagsMix,DistributionPlotBinomial,DistributionPlotGamma,Distrib
 S3method(print, dosagesMCMC)
 S3method(print, runJags)
 S3method(print, runJagsWrapper)
+S3method(plot, runJagsWrapper)
 S3method(print, segratioMCMC)
 S3method(plot, segratioMCMC)
 S3method(summary, segratioMCMC)
@@ -10,3 +11,7 @@ importFrom(gtools, logit)
 ##importFrom(coda, HPDinterval, acfplot, raftery.diag, geweke.diag, heidel.diag, levelplot, cumuplot, traceplot, densityplot.mcmc, densityplot.mcmc.list, autocorr, varnames, xyplot.mcmc, xyplot.mcmc.list, qqmath.mcmc, qqmath.mcmc.list)
 importFrom(coda, HPDinterval, acfplot, raftery.diag, geweke.diag, heidel.diag, cumuplot, traceplot, autocorr, varnames, read.openbugs)
 importFrom(lattice, histogram, panel.histogram, panel.densityplot, panel.lines, xyplot, panel.xyplot, panel.curve, qqmath, levelplot, densityplot)
+importFrom("grDevices", "nclass.Sturges")
+importFrom("graphics", "abline", "plot", "points")
+importFrom("stats", "dbinom", "dgamma", "dnorm", "pnorm", "qbinom", "qgamma",
+           "qnorm")

R/plotTheoretical.R

@@ -135,7 +135,7 @@ plotTheoretical <-
         comp.lines[[iii+1]]
       comp.lines[[1]] <- comp.lines[[1]] + comp.lines[[iii+1]]
     }
-    warning("Binomial mixture density is only approximate on logit scale")
+    cat("PlotTheoretical Warning: Binomial mixture density is only approximate on logit scale\n")
 
     if (plot.sr) {
       ## first attempt - too global??

README.md

@@ -0,0 +1,10 @@
+# R package: polySegratioMM
+
+
+**polySegratioMM:** Bayesian mixture models for marker dosage in autopolyploids
+
+Fits Bayesian mixture models to estimate marker dosage for dominant markers on autopolyploids using JAGS (1.0 or greater) as outlined in Baker et al (2010). May be used in conjunction with polySegratio for simulation studies and comparison with standard methods.
+
+	Maintenance release: I am no longer working in polyploids.
+
+**NB:** Migrated from [r-forge](http://r-forge.r-project.org/projects/polysegratio/) to better manage project

inst/CITATION

@@ -3,31 +3,30 @@ citHeader("To cite package 'polySegratioMM' in publications use:")
 year <- sub(".*(2[[:digit:]]{3})-.*", "\\1", meta$Date)
 vers <- paste("R package version", meta$Version)
 
-citEntry(entry="Article",
-              title = "Bayesian estimation of marker dosage in sugarcane and other autopolyploids",
-              author = personList(as.person("Peter Baker"),
-                                  as.person("Phillip Jackson"),
-                                  as.person("Karen Aitken")),
-              journal = "TAG Theoretical and Applied Genetics",
-              year = "2010",
-	      volume = "120",
-	      pages = "1653-1672",
-
-              textVersion =
-              paste("Peter Baker, Phillip Jackson and Karen Aitken (2010)",
-                    " Bayesian estimation of marker dosage in sugarcane and other autopolyploids.",
-                    " Theoretical and Applied Genetics 120 1653-1672", sep="")
+citEntry(
+  entry="Article",
+  title = "Bayesian estimation of marker dosage in sugarcane and other autopolyploids",
+  author = personList(as.person("Baker, P."),
+                      as.person("Jackson, P."), 
+                      as.person("Aitken, K.")),
+  journal = "TAG Theoretical and Applied Genetics",
+  year = "2010",
+  volume = "120",
+  pages = "1653--1672",
+  url =		 "https://doi.org/10.1007/s00122-010-1283-z",
+  doi =		 "10.1007/s00122-010-1283-z",
+  textVersion="Baker, P., Jackson, P. & Aitken, K. Theor Appl Genet (2010) 120: 1653-1672. https://doi.org/10.1007/s00122-010-1283-z"
 )
 
-citEntry(entry="Manual",
-   title = "polySegratioMM Bayesian mixture models for marker dosage in autopolyploids",
+citEntry(
+  entry="Manual",
+  title = "polySegratioMM Bayesian mixture models for marker dosage in autopolyploids",
   author = personList(as.person("Peter J Baker")),
-
-         year = year,             
-         note = vers,             
+  year = year,             
+  note = vers,             
+  textVersion =            
+    paste("Peter J Baker (",
+          year,
+          "). polySegratioMM: Bayesian mixture models for marker dosage in autopolyploids. ",
+          vers, ".", sep="" ))
 
-         textVersion =            
-         paste("Peter J Baker (",
-               year,
-               "). polySegratioMM: Bayesian mixture models for marker dosage in autopolyploids. ",
-               vers, ".", sep="" ))

inst/doc/polySegratioMM-overview.R

@@ -1,13 +1,13 @@
 ### R code from vignette source 'polySegratioMM-overview.Rnw'
 
 ###################################################
-### code chunk number 1: polySegratioMM-overview.Rnw:63-64
+### code chunk number 1: polySegratioMM-overview.Rnw:64-65
 ###################################################
 library(polySegratioMM)
 
 
 ###################################################
-### code chunk number 2: polySegratioMM-overview.Rnw:67-72
+### code chunk number 2: polySegratioMM-overview.Rnw:68-73
 ###################################################
 ##library(cacheSweave)  #  comment this out after development phase
 ## to use:    Sweave("polySegratioMM-overview.Rnw", driver=cacheSweaveDriver)
@@ -17,13 +17,13 @@ options(width=70, digits=4)
 
 
 ###################################################
-### code chunk number 3: polySegratioMM-overview.Rnw:90-91
+### code chunk number 3: polySegratioMM-overview.Rnw:91-92
 ###################################################
 data(hexmarkers)
 
 
 ###################################################
-### code chunk number 4: polySegratioMM-overview.Rnw:93-100
+### code chunk number 4: polySegratioMM-overview.Rnw:94-101
 ###################################################
 ##<<simData, cache=true>>=
 ## simulate small autohexaploid data set of 500 markers for 200 individuals
@@ -35,21 +35,21 @@ print(hexmarkers)
 
 
 ###################################################
-### code chunk number 5: polySegratioMM-overview.Rnw:108-109
+### code chunk number 5: polySegratioMM-overview.Rnw:109-110
 ###################################################
 sr <-  segregationRatios(hexmarkers$markers)
 
 
 ###################################################
-### code chunk number 6: polySegratioMM-overview.Rnw:115-118
+### code chunk number 6: polySegratioMM-overview.Rnw:116-119
 ###################################################
 print(plotTheoretical(ploidy.level=6, seg.ratios=sr, main="",
   	    expected.segratio=NULL, proportions=c(0.7,0.2,0.1),
   	    n.individuals=200))
 
 
 ###################################################
-### code chunk number 7: polySegratioMM-overview.Rnw:141-148
+### code chunk number 7: polySegratioMM-overview.Rnw:142-149
 ###################################################
 ##<<simDataOver, cache=true>>=
 ## simulate small autohexaploid data set of 500 markers for 200 individuals
@@ -61,27 +61,27 @@ data(hexmarkers.overdisp)
 
 
 ###################################################
-### code chunk number 8: polySegratioMM-overview.Rnw:154-155
+### code chunk number 8: polySegratioMM-overview.Rnw:155-156
 ###################################################
 sr.overdisp <-  segregationRatios(hexmarkers.overdisp$markers)
 
 
 ###################################################
-### code chunk number 9: polySegratioMM-overview.Rnw:160-163
+### code chunk number 9: polySegratioMM-overview.Rnw:161-164
 ###################################################
 print(plotTheoretical(ploidy.level=6, seg.ratios=sr.overdisp, main="",
   expected.segratio=NULL, proportions=c(0.7,0.2,0.1),
   n.individuals=200))
 
 
 ###################################################
-### code chunk number 10: polySegratioMM-overview.Rnw:267-268
+### code chunk number 10: polySegratioMM-overview.Rnw:268-269
 ###################################################
 x.mod1 <- setModel(3,6)  # autohexaploid model with 3 components
 
 
 ###################################################
-### code chunk number 11: polySegratioMM-overview.Rnw:292-297
+### code chunk number 11: polySegratioMM-overview.Rnw:293-298
 ###################################################
 ## produced using the following but loaded as data to avoid the run time on slow machines
 ##mcmcHexRun <- runSegratioMM(sr.overdisp, x.mod1, burn.in=200, sample=500, plots=FALSE)
@@ -91,43 +91,43 @@ data(mcmcHexRun)
 
 
 ###################################################
-### code chunk number 12: polySegratioMM-overview.Rnw:308-309
+### code chunk number 12: polySegratioMM-overview.Rnw:309-310
 ###################################################
 print(mcmcHexRun$run.jags)
 
 
 ###################################################
-### code chunk number 13: polySegratioMM-overview.Rnw:313-314
+### code chunk number 13: polySegratioMM-overview.Rnw:314-315
 ###################################################
 print(mcmcHexRun$summary)
 
 
 ###################################################
-### code chunk number 14: polySegratioMM-overview.Rnw:321-322
+### code chunk number 14: polySegratioMM-overview.Rnw:322-323
 ###################################################
 print(mcmcHexRun$diagnostics)
 
 
 ###################################################
-### code chunk number 15: polySegratioMM-overview.Rnw:326-327
+### code chunk number 15: polySegratioMM-overview.Rnw:327-328
 ###################################################
 print(mcmcHexRun$doses)
 
 
 ###################################################
-### code chunk number 16: polySegratioMM-overview.Rnw:338-339
+### code chunk number 16: polySegratioMM-overview.Rnw:339-340
 ###################################################
 print(plot(mcmcHexRun$mcmc.mixture$mcmc.list[[1]][,c("P[1]","mu[1]","sigma","T[140]")]))
 
 
 ###################################################
-### code chunk number 17: polySegratioMM-overview.Rnw:364-365
+### code chunk number 17: polySegratioMM-overview.Rnw:365-366
 ###################################################
 print(plot(mcmcHexRun, theoretical=TRUE, main=""))
 
 
 ###################################################
-### code chunk number 18: polySegratioMM-overview.Rnw:396-400
+### code chunk number 18: polySegratioMM-overview.Rnw:397-401
 ###################################################
 cat("Employing maximum posterior probability\n")
 table(Dose=mcmcHexRun$doses$max.post.dosage, exclude=NULL)
@@ -136,7 +136,7 @@ table(Dose=mcmcHexRun$doses$dosage[,"0.8"], exclude=NULL)
 
 
 ###################################################
-### code chunk number 19: polySegratioMM-overview.Rnw:409-418
+### code chunk number 19: polySegratioMM-overview.Rnw:410-419
 ###################################################
 cat("Employing theChi squared test\n")
 dose.chi <- test.segRatio(sr.overdisp, ploidy.level = 6)

inst/doc/polySegratioMM-overview.Rnw

@@ -54,10 +54,11 @@ distribution.
 
 This library calls the \texttt{JAGS} software for Bayesian
 calculation. \texttt{JAGS 1.0} or higher must be installed following
-instructions from \url{http://www-fis.iarc.fr/~martyn/software/jags/}.
-The \texttt{JAGS} executable must be in your path. Currently, no
-checking is carried out to ascertain whether or not \texttt{JAGS} is
-set up appropriately.
+instructions from \url{http://mcmc-jags.sourceforge.net/}. Note that
+only the most recent version is used for testing with \texttt{R}.  The
+\texttt{JAGS} executable must be in your path. Currently, no checking
+is carried out to ascertain whether or not \texttt{JAGS} is set up
+appropriately.
 
 To use the library, you need to attach it with
 <<>>=

man/polySegratioMM-package.Rd

@@ -3,7 +3,7 @@
 \alias{polySegratioMM}
 \docType{package}
 \title{
-Marker dosage for autoployploids by Bayesian mixture models 
+Bayesian Mixture Models for Marker Dosage in Autopolyploids
 }
 \description{
   These functions provide tools for estimating marker dosage for
@@ -20,8 +20,8 @@ Marker dosage for autoployploids by Bayesian mixture models
   \tabular{ll}{
 Package: \tab polySegratioMM\cr
 Type: \tab Package\cr
-Version: \tab 0.6-2\cr
-Date: \tab 2012-04-10\cr
+Version: \tab 0.6-4\cr
+Date: \tab 2018-03-22\cr
 License: \tab  GPL-3
 }
 
@@ -74,8 +74,7 @@ segregation ratios and fitted mixture model on the logit scale.
       autopolyploids. \emph{Journal of genetics} \bold{22} 359--372}
     \item{Ripol, M I et al } { (1999) Statistical aspects of genetic mapping in
       autopolyploids. \emph{Gene} \bold{235} 31--41 }
-    \item{JAGS} { \url{http://www-fis.iarc.fr/~martyn/software/jags/} and
-      \url{http://streaming.stat.iastate.edu/wiki/index.php/JAGS\_Guide}}
+    \item{JAGS} { \url{http://mcmc-jags.sourceforge.net/}}
   }
 }
 \examples{