search for: strain

We need to keep the discussion on the list. When I run your code, there are several problems. strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName ="strain", header = T, row.names = 1) str(strain.data) # lists 9 columns at the end with all NAs strain.data1 <- (strain.data, sqrt.dist = TRUE) # this is not a valid R line. I get Error: unexpected ',' in "strai...

I've scoured the archives but have found no concrete answer to my question. Problem: Two data sets 1st data set(x) = 20,000 rows 2nd data set(y) = 5,000 rows Both have the same column names, the column of interest to me is a variable called strain. For example, a strain named "Chab1405" appears in x 150 times and in y 25 times... strain "Chab1999" only appears 200 times in x and none in y (so i dont want that retained). I want to create a new data frame that has all 175 measurements for "Chab1405" and any oth...

...araway 2005; and the R book, Crawley 2007), I am still not sure of the syntax to test my hypothesis. Thanks in advance for reading me. Briefly, I describe the data and the situation: I want to describe the age-specific fecundity of the ith individual from the jth replicate (or line) from the kth strain. Variables: Categorical factors: A[a] = Age (1,2,3 n=8) #Because the fecundity is not linear, I decided to include it in the model as a factor s[k] =strain (A and B, n=2) # for the moment two, but it?s likely to increase as the work progresses l[j] = line (1,2,..n=10) i[i] = Ind(1,2 n=50)...

Hi, I have a data-frame, r (column names below), that needs subsetting: date, time, strain, gene, deltact When I try to subset r by applying selection criteria on two columns I get an empty data frame. For example I would like to extract all rows that have time == 0h and strain == ROC. So, t <- subset(r, (r$time == "0h" && r$strain == "ROC"), select= c(tim...

dfhfsdhf at ghghgr.com I ran a simple lme model: modelrandom=lmer(y~ (1|Test) + (1|strain), data=tempsub) Extracted the BLUPs: blups=ranef(modelrandom)[1] Even wrote myself a nice .csv file....: write.csv(ranef(modelrandom)[1],paste(x,"BLUPs.CSV")) This all works great. I end up with a .csv file with the names of my strains in the first column and the BLUP in the second c...

Dear R user, I have a question on using R to analyze data with repeated measurements. I have 2 species with several strains (12) per species, each of which has been measured twice with for a given trait. No particular covariance, just two measures. Now I want to analyze the data with an ANOVA (aov) considering these repeated measures to get the MSq and SSq for the species and strain level. I would like to know how...

Hello Sir I am getting problem in plotting in CCA . Could you please help me? I wrote the below command but I don't know why it is taking only first 5 env data rather than all 9. > strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName="strain", header = T, row.names = 1) > env.data <- read.xlsx("Dee rhiz.xlsx", sheetName="env", header = T, row.names = 1) > strain.cca <- cca(strain.data ~ Ph+TotalN+Organicmatter+Ca+K+Na+P+Cu+Mn, da...

Hello, I am new to R and currently have the following problem: I have successfully loaded my data in R which consists of two numeric columns (LI_F and female) and one character column (Strain). So far I can plot two different set of boxplots for each of the numeric columns plotted by the groups of the character column and the commands look like that: boxplot(LI_F~Strain, ylab="LI_F", xlab="Strain", data=pain) boxplot(female~Strain, ylab="female", xlab=&quo...

...loddsratio objects, but I'm having problems figuring out how to do this generally. # install.packages("vcdExtra", repos="http://R-Forge.R-Project.org") library(vcdExtra) > fung.lor <- loddsratio(Fungicide) > fung.lor log odds ratios for group and outcome by sex, strain strain sex 1 2 M -1.596015 -0.8266786 F -1.386294 -0.6317782 > > fung.lor.df <- as.data.frame(fung.lor) > fung.lor.df group outcome sex strain LOR ASE 1 Control:Treated Tumor:NoTumor M 1 -1.5960149 0.7394909 2 Control:Treated Tumor:NoTumor F 1 -1.3862944 0.9574271 3 Control:Treated...

...a version of SSmicmen that allows testing for group differences? The basic Michaelis-Menten equation is: (Bmax * X) / (Kd + X). The nlme package allows modeling of random effects for Bmax and Kd as needed, but I curious how I can build in group differences? I have receptor binding data for strains of mice, and following Pinheiro and Bates' lead in their book, a random effort for animal differences in Bmax seems reasonable, within strain. However, I'd like a self-start function, or even just the equation above, modified to allow testing for strain differences in Bmax and or K...

Hello, I seem unable to construct a legend which contains a substitution as well as math symbols. I'm trying to do the following: strain2 <- "YJG48" legend.txt <- c( substitute( strain * %==% * "YJG45, rpn10" * %Delta%, list(strain=strain2) ), "Verhulst/Logistic", "Malthus" ) legend( 100,2.5, legend.txt, cex=0.75, bty="n", pch=c(20,NA,NA), lty=c(NA,1,2) I...

...rk: It is a light/dark choice test conducted in insect larvae.  The response is binary (0- present in dark area, 1-present in light area) and the experiment is run for 15 min, so there are 15 repeated measurements per individual larva at 1 min intervals.  The factors which affect this study are Strain (2 levels-G and S),  wavelength of light (4 levels-blue, green, UV, red), and starting response at 0 min (two levels- animal present in dark-D or light-L).  This is how I think it is nested.  Strain nested inside Wavelength, Subject (individual) nested within strain, Starting response within su...

...that the F values agree with the expected mean square errors? Specifically, suppose I have a design where "Heads" are nested within "Machines". I would like to model the following Y_ijk = Mu + Machine_i +Head_j(i) +Error_k(ij). Using the commands below, > summary(aov(Strain~Machine + Head%in%Machine )) Df Sum Sq Mean Sq F value Pr(>F) Machine 4 45.07 11.27 1.0532 0.38762 Machine:Head 15 282.87 18.86 1.7625 0.06252 . Residuals 60 642.00 10.70 the F value to test "Machine" uses the MS residual instead of MS Head(Mac...

...----- Original Message ----- From: <asterisk-users-request@lists.digium.com> To: <asterisk-users@lists.digium.com> Sent: Thursday, August 11, 2005 3:59 PM Subject: Asterisk-Users Digest, Vol 13, Issue 81 > Message: 24 > Date: Thu, 11 Aug 2005 20:48:14 +0100 > From: "Andi Strain" <atspublic@dsl.pipex.com> > Subject: [Asterisk-Users] Privacy Manager > To: <Asterisk-Users@lists.digium.com> > Message-ID: <20050811194816.C18EEE00024B@galaxy.systems.pipex.net> > Content-Type: text/plain; charset="us-ascii" > > I'm trying to...

Dear List, I downloaded R for the first time yesterday, in the hopes that I might deal more effectively with a complex repeated measures experimental design involving inbred strains of laboratory mice. The design below, somewhat simplified, cannot be computed with standard ANOVA, because something called the X'X matrix is too large. The design has the following factors: Between-subject factors (levels): inbred mouse strain (20, "twenty") sex (2) Animals:...

I have assayed the concentrations of various metal elements in different anatomic regions of two strains of mice. Now, for each element, in each region, I want to do a t test to find whether there is any difference between the two strains. Here is what I did (using simulated data as an example): # create the data frame > elemconc = data.frame(expand.grid(id=1:3, geno=c('exp', 'wt'...

...X Line X5a Line X5b X5 X If all the line pairs were independently derived, a model could be geneExpression ~ Line.Pair + AlcoholPreference with the factor of interest being Alcohol Preference but, there is the "X" factor, with the 2 "X strain-pairs being related, whereas the others are unrelated to each other and also to the 2 "X" strain-pairs. We want to take into account the fact that there are really only 4 parent populations of these 5 strain-pairs so as to decrease the weighting put on the "X" strains in the mo...

...pecifies the model and s (created by prelim.mix) and x only contain info on incomplete the data set I want to impute. As best as I can tell this is not the case. For instance, I create a 'model object' (a general location parameter list) from the data set trainSet using em.mix as follows: sTrain <- prelim.mix(trainSet,nCategorical) thetaTrain <- em.mix(sTrain,maxits=1000,showits=TRUE,eps=0.0001) I then attempt to use this model to impute a missing field (TC) in the data set workSet as follows: workSet$TC <- NA sWork <- prelim.mix(workSet,nCategorical) imputedWork <- imp.mi...

Dear R users, Here is the coxme output I obtain on my survival dataset having 3 strains and 2 infection status (i: infected, ni: non infected) coxme(Surv(lay) ~ infection*strain, data=datalay, random= ~1 |block) Cox mixed-effects model fit by maximum likelihood Data: datalay n= 1194 Iterations= 3 77 NULL Integrated Penalized Log-likelihood -7270.028 -7223.85...

...ach level of a factor For example, i have three levels of a variable I call 'Code'...I want to model the data under each level of code differently...I've attached a sample data set... http://r.789695.n4.nabble.com/file/n3913431/data.txt data.txt I.E for code 0HY0 I want to model y~ 1|strain + 1|code *both code and strain are random effects... for code 0HY1 run a separate model with different y's.... y~ 1|strain + 1|code tapply does not work (or rather i cannot get it to work) In SAS i would simply use PROC MIXED data=data; by code; model y=; random code strain /solution; run;...