I'm trying to up the number of starting values in Mplus when I pass objects through the program using the mplusModeler package in R, specifically the mplusObject function. Is there a way to specify the number of starts (e.g., 100 10) instead of the defaults? Or is this something I can only do in Mplus and there's no way to do this from R?
I figured it out!
You add the command to the ANALYSIS section of the input. For example:
lpa_model <- mplusObject(
TITLE = "3-Class LPA;",
VARIABLE = "USEVARIABLES = x01-x15;
CLASSES=c(3);",
ANALYSIS = "ESTIMATOR = MLR;
TYPE = MIXTURE;
STARTS=100 10;",
MODEL = " [code continues...]
Related
I am trying to turn off the display of plot in R.
I read Disable GUI, graphics devices in R but the only solution given is to write the plot to a file.
What if I don't want to pollute the workspace and what if I don't have write permission ?
I tried options(device=NULL) but it didn't work.
The context is the package NbClust : I want what NbClust() returns but I do not want to display the plot it does.
Thanks in advance !
edit : Here is a reproducible example using data from the rattle package :)
data(wine, package="rattle")
df <- scale (wine[-1])
library(NbClust)
# This produces a graph output which I don't want
nc <- NbClust(df, min.nc=2, max.nc=15, method="kmeans")
# This is the plot I want ;)
barplot(table(nc$Best.n[1,]),
xlab="Numer of Clusters", ylab="Number of Criteria",
main="Number of Clusters Chosen by 26 Criteria")
You can wrap the call in
pdf(file = NULL)
and
dev.off()
This sends all the output to a null file which effectively hides it.
Luckily it seems that NbClust is one giant messy function with some other functions in it and lots of icky looking code. The plotting is done in one of two places.
Create a copy of NbClust:
> MyNbClust = NbClust
and then edit this function. Change the header to:
MyNbClust <-
function (data, diss = "NULL", distance = "euclidean", min.nc = 2,
max.nc = 15, method = "ward", index = "all", alphaBeale = 0.1, plotetc=FALSE)
{
and then wrap the plotting code in if blocks. Around line 1588:
if(plotetc){
par(mfrow = c(1, 2))
[etc]
cat(paste(...
}
and similarly around line 1610. Save. Now use:
nc = MyNbClust(...etc....)
and you see no plots unless you add plotetc=TRUE.
Then ask the devs to include your patch.
I want to perform a PCA analysis in adegenet starting from a genepop file without defined populations.
I imported the data like this:
datapop <- read.genepop('tous.gen', ncode=3, quiet = FALSE)
it works, and I can perform a PCA after scaling the data.
But I would like to plot the results / individuals on the PCA axis according to their population of origin using s.class. I have a vcf file with a three lettre code for each individual. I imported it in R:
pops_list <- read.csv('liste_pops.csv', header=FALSE)
but now how can I use it to define population levels in the genind object datapop?
I tried something likes this:
setPop(datapop, formula = NULL)
setPop(datapop) <- pops_list
but it doesn't work; even the first line doesn't work: I get this message:
"Erreur : formula must be a valid formula object."
And then how should I use it in s.class?
thanks
Didier
Without a working example it is kind of hard to tell but perhaps you can find the solution to your problem here: How to add strata information to a genind
Either way from your examples and given how the setPop method works, your line setPop(datapop, formula = NULL) would not work because you would not be defining anything. You would actually have to do:
setPop(datapop) <- pops_list
while also guaranteeing that pops_list is a factor with the appropriate format
I know this is a bit late, but the way to do this is to add pops_list as the strata and then use setPop() to select a certain column:
strata(datapop) <- pops_list
setPop(datapop) <- ~myPop # set the population to the column called "myPop" in the data frame
I am trying to use Gage package implemented in R to analyze my RNA-seq data. I followed the tutorial and got my data.kegg.p file and I used the following script to generate the heatmap for the top gene set
for (gs in rownames(data.kegg.p$greater)[1]) {
outname = gsub(" |:|/", "_", substr(gs, 10, 100))
geneData(genes = kegg.gs[[gs]], exprs = essData, ref = 1,
samp = 2, outname = outname, txt = T, heatmap = T,
Colv = F, Rowv = F, dendrogram = "none", limit = 3, scatterplot = T)
}
I did get a pdf file named "NOD-like_receptor_signaling_pathway.geneData.heatmap.pdf", but when I open this file with acrobat reader or photoshop, it gives the error information that this file has been disrupted and cannot be recovered. Could anyone help check this file (https://www.dropbox.com/s/wrsml6n1pbrztnm/NOD-like_receptor_signaling_pathway.geneData.heatmap.pdf?dl=0) to see whether it is really disrupted and is it possible to find a way to recover it?
I also attached the R workspace file (https://www.dropbox.com/s/6n5m9x5hyk38ff1/A549.RData?dl=0). The object "a4" is the data with the format ready for gage analysis. It contains the data of the reference sample (nc) the treated sample (a549). It can be accepted by gage for analysis but generate the heatmap pdf file which cannot be opened (above). Would you mind helping me check whether these data can be properly used to generated the correct gage result?
Best regards.
I'm running into a similar problem myself. Not 100% sure but I think this problem occurs when there is no heatmap to plot. In my case, I was doing as.group comparison with ref and sample selections. I think the software treats this circumstance as a sample n of 1 and can't really show a differential heatmap. When I tried using 1ongroup setting, I was able to visualize the pdf file.
I have a graph that is created by complex numbers from the function below. I would like to extract the resulting data points which correpond with the line from the data plot as to be able to work with a vector of data.
library(multitaper)
NW<-10
K<-5
x<-c(2,3,1,3,4,6,7,8,5,4,3,2,4,5,7,8,6,4,3,2,4,5,7,8,6,4,5,3,2,5,7,8,6,4,5,3,6,7,8,8,9,7,6,5,4,7)
resSpec <- spec.mtm(as.ts(x), k= K, nw=NW, nFFT = length(x),
centreWithSlepians = TRUE, Ftest = TRUE,
jackknife = FALSE, maxAdaptiveIterations = 100,
plot =FALSE, na.action = na.fail)
plot(resSpec)
What would be the best procedure. I have tried saving the plot in emf. I wanted to use package ReadImages which was I believe the right package. (however this was not available for R versión 3.02 so I could not use it). What would be the correct procedure of saving and extracting and are there other packages and in what file types could I save the graph (as far as I can see R (OS windows) only permist emf.)
Any help welcomed
I'm an R programming beginner and I'm trying to implement the clustering.plot method available in R package EMA. My clustering works fine and I can see the results populated as well. However, when I try to generate a heat map using clustering.plot, it gives me an error "Error in plot.new (): graphic edges too large". My code below,
#Loading library
library(EMA)
library(colonCA)
#Some information about the data
data(colonCA)
summary(colonCA)
class(colonCA) #Expression set
#Extract expression matrix from colonCA
expr_mat <- exprs(colonCA)
#Applying average linkage clustering on colonCA data using Pearson correlation
expr_genes <- genes.selection(expr_mat, thres.num=100)
expr_sample <- clustering(expr_mat[expr_genes,],metric = "pearson",method = "average")
expr_gene <- clustering(data = t(expr_mat[expr_genes,]),metric = "pearson",method = "average")
expr_clust <- clustering.plot(tree = expr_sample,tree.sup=expr_gene,data=expr_mat[expr_genes,],title = "Heat map of clustering",trim.heatmap =1)
I do not get any error when it comes to actually executing the clustering process. Could someone help?
In your example, some of the rownames of expr_mat are very long (max(nchar(rownames(expr_mat)) = 271 characters). The clustering_plot function tries to make a margin large enough for all the names but because the names are so long, there isn't room for anything else.
The really long names seem to have long stretches of periods in them. One way to condense the names of these genes is to replace runs of 2 or more periods with just one, so I would add in this line
#Extract expression matrix from colonCA
expr_mat <- exprs(colonCA)
rownames(expr_mat)<-gsub("\\.{2,}","\\.", rownames(expr_mat))
Then you can run all the other commands and plot like normal.