search for: tissu

I am trying to sample a subset from a matrix using sample. The size of the matrix is 20X 1532. It works fine with this, but when I transpose the matrix and try to sample it, it returns null. pick.set<-sample(tissue.exp.t,5,replace=FALSE,prob=NULL) Is there something that I am missing here ? Thanks ../Murli

Hello, I'm using aov() to analyse changes in brain volume between males and females. For every subject (there are 331 in total) I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). The data looks like this: Subject Sex Lobe Tissue Volume subect1 1 F g 262374 subect1 1 F w 173758 subect1 1 O g 67155 subect1 1 O w 30067 subect1 1 P g 117981 subect1 1 P w 85441 subect1 1 T g 185241 subect1 1 T w 83183 subect2 1 F g 255309 subect2 1 F w 164335 subect2 1 O...

Hi, I am doing an analysis to see if these is tissue specific effects on the gene expression data . Our data were collected from 6 different labs (batch effects). lab 1 has tissue type 1 and tissue type 2, lab 2 has tissue 3, 4,5,6. The other labs has one tissue type each. The 'sample' data is as below: ------------------------------------...

I'm working with a nested model (mixed). I have four factors: Patients, Tissue, sex, and tissue_stage. Totally I have 10 patients, for each patient, there are 2 tissues (Cancer vs. Normal). I think Tissue and sex are fixed. Patient is nested in sex,Tissue is nested in patient, and tissue_stage is nested in Tissue. I tried aov and lme as the following, > aov(gene ~ t...

Hello, I've used this command to analyse changes in brain volume: mod1<-aov(Volume~Sex*Lobe*Tissue+Error(Subject/(Lobe*Tissue)),data.vslt) I'm comparing males/females. For every subject I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). As aov() provides only type I anovas, I would like to use lmer() with type II, however, I have struggled...

Dear R users, I have a data frame in the form below, on which I would like to make normality tests on the values in the ExpressionLevel column. > head(df) ID Plant Tissue Gene ExpressionLevel 1 1 p1 t1 g1 366.53 2 2 p1 t1 g2 0.57 3 3 p1 t1 g3 11.81 4 4 p1 t2 g1 498.43 5 5 p1 t2 g2 2.14 6 6 p1 t2 g3 7.85 I would like to make the tests on every group according to the content of the Plant...

Hello, I'm fitting linear mixed models to gene-expression data from microarrays, in a data set where 4608 genes are studied. For a sample of 5 subjects and for each gene we observe the expression level (Intensity) in four different tissues: N, Tp, Tx and M. I want to test whether the expression level is different accross tissues. Between-subject variability is modeled with a random intercept, and the within-subject by allowing heteroscedastic and correlated errors accross tissues. The proposed model can then be fitted by lme(In...

...residual (between-subject) effects at site B correlation between site A and B residuals (between-subject) effects My problem is formulating the random = argument to give estimates of all 9 random components ... Hope someone can help ... Robert Kinley Study: Pos tissue VC, Neg tissue VC, Pos/Neg tissue correlation Study*Group: Pos tissue VC, Neg tissue VC, Pos/Neg tissue correlation Residual (animal): Pos tissue VC, Neg tissue VC, Pos/Neg tissue correlation [[alternative HTML version deleted]]

...","Y; DEMENTIA","Y","","Y; DX AGE: 33; CHOREA", "Y", "Y; WEAKNESS") As can be seen, the semi-colon delimiter follows its own set of rules, which are internally consistent - with all 3 elements of data, it should be "Status; Age; Tissue Type". However, if there is only tissue type, it is" Status; Tissue Type", without the trailing semi-colon. However, if there is Age available, it is "Status; Age;". The main challenge for me is how to parse/convert this dataset into a useful and consistent data.frame, or...

Hi, There are 20 subjects grouped by Gender, each subject has 2 tissues (normal vs. cancer). In fact, it is a 2-way anova (factors: Gender and tissue) with tissue nested in subject. I've tried the following: Model 1: lme(response ~ tissue*Gender, random = ~1|subject) Model 2: response ~ tissue*Gender + subject Model 3: response ~ tissue*Gender It seems like M...

...ze" correlation coefficients from different sample sets? Could an expression such as "corr * (1 - pval)" be used for normalization? Maybe, it is not possible to normalize correlation coefficients? Would a barplot comparing the correlation coefficients between two genes for different tissues be meaningful? (Alternatively, I have tried to use (1-pval) to calculate the gray-level of the bars.) Any further suggestions would be appreciated very much. Best regards Christian Stratowa -----Original Message----- From: Stratowa,Dr.,Christian FEX BIG-AT-V Sent: Monday, July 19, 2004 15:00...

Hi Dear all, I have some gene expression data samples from different tissue types ----------------------------------------------- - 120 samples from blood (B) - 20 samples from Liver (L) - 15 samples from Kidney (K) - 6 samples from heart (H) ----------------------------------------------- All the samples are from different individuals, so there are in total 161 individua...

...unt for hierarchical effects at the same time. Additionally, I'd like also to know if it would be possible to perform any feature selection on this model fit. I have a data set that is composed by multiple marker measurements (and hundreds of covariates) at different time points from different tissue samples of different patients. Suppose that the data were coming from animal model with very few subjects (n=6) that were followed up given a pathogen exposure, measured several times, sampling different tissues in the same days, until a certain outcome was reached (or outcome censored). Suppose t...

...with the caveat that I'm not a statistician by training, but have a fairly decent understanding of probability and likelihood. Nevertheless, I'm trying to fit a nonlinear model to a dataset which has two main factors using nlme. Within the dataset there are two Type categories and four Tissue categories, thus giving me 8 datasets in total. The dataset is in a groupedData object with formula= Count ~ Time|Type/Tissue and there are three basic model parameters that I am trying to fit: T0, aN, and aL. Calling nlsList gives ------------------------------------------ >nlsLis...

...efficients from different > sample sets? Could an expression such as "corr * (1 - pval)" be used > for normalization? Maybe, it is not possible to normalize correlation > coefficients? Would a barplot comparing the correlation coefficients > between two genes for different tissues be meaningful? (Alternatively, > I have tried to use (1-pval) to calculate the gray-level of the bars.) > > Any further suggestions would be appreciated very much. > > Best regards > Christian Stratowa > > -----Original Message----- > From: Stratowa,Dr.,Christian FEX B...

...le cut out from database: CODE NAME DATE DATA1 4813 ADVANCED TELECOM 1987 0.013 3845 ADVANCED THERAPEUTIC SYS LTD 1987 10.1 3845 ADVANCED THERAPEUTIC SYS LTD 1989 2.463 3845 ADVANCED THERAPEUTIC SYS LTD 1988 1.563 2836 ADVANCED TISSUE SCI -CL A 1987 0.847 2836 ADVANCED TISSUE SCI -CL A 1989 0.872 2836 ADVANCED TISSUE SCI -CL A 1988 0.529 What I need is: 1) Delete all cases containing -CL A (and also -OLD, -ADS, etc) at the end 2) Delete all cases that have less than 3 years...

Hello, unfortunately I have I big problem I can't solve. I have to analyse if a gene is tissue specific. For example for the gene xyz I have following expression values: Heart Liver Brain 8.998497 10.013561 12.277407 9.743556 10.137574 11.033957 For every tissue I have two values from two different experiments. Now I want to test if Heart is significant higher th...

dear members, i would like to write a variable in a plot title (main="") but i don't know the right syntax:(...i tried a lot of different ways without success. here my example: y=30 z=33 for (i in 10:length(tissue)) { png(filename = tissues[i], width = 1024, height = 768, pointsize = 12, bg = "white") gene.graph("ENSG00000115252", rma.affy, gps=list(1:3, y:z), type="mean-int", gp.col=c("red", "blue"), by.order=TRUE, scale.to.gene=FALSE, use.symbol=TRUE, u...

Hi, I have a question about how to do covariate adjustment. I have two sets of 'gene expression' data. They are from two different tissue types, 'liver' and 'brain', respectively. The purpose of my analysis is to compare the pattern of the whole genome 'gene expression' between the two tissue types. I have 'age' and 'sex' as covariates. Since 'age' and 'sex' definitely have i...

Hello, I am using Mechanize to post a form to a website. When I do this by hand in my browser the response takes about 35s to come back (it''s a long page full of tables and graphics). When I do this with Mechanize, the server starts to respond and then appears to hang. The obvious conclusion is that my code is wrong but I am reasonably sure that I haven''t altered it