similar to: Very large matrices for very large genome

Dear all I apologize for cross-posting, but first it is accepted custom to thank the repliers and give a summary, and second I have still the feeling that this problem might be a general statistical problem and not necessarily related to microarrays only, but I might be wrong. First, I want to thank Robert Gentleman, Mark Kimpel and Mark Reiners for their kind replies. Robert Gentleman kindly

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,

Genome Institute of Singapore (GIS) Biostatistics Group The Genome Institute of Singapore ( http://www.gis.a-star.edu.sg <http://www.gis.a-star.edu.sg> ) is looking for statisticians who are interested in a wide range of biomedical probems. We are especially interested in hearing from senior researchers interested in leading their own group. The institute is well-funded and engaged

We are seeking a talented and driven postdoctoral fellow to join the laboratory of Jake Michaelson, PhD, assistant professor in the department of psychiatry at the University of Iowa. The Michaelson lab investigates the effect of genetic variation on the development and function of the brain, particularly in the context of neurodevelopmental conditions such as autism and language impairment. Our

Dear all, I am currently analyzing a set of arrays hybe on the lattest affy Drosophila 2.0 GeneChip. I am trying to run simple annaffy analysis but can¹t find what is the name of the annotation file I need to use. Here is the output of the AffyBatch object I am using: > expData AffyBatch object size of arrays=732x732 features (16749 kb) cdf=Drosophila_2 (18952 affyids) number of samples=4

Hi, I have a set of genes and its chromosomal physical position in a text file. I want to view those genes in the chromosome using R package GenePlotter. Could any one please tell how to view this. Thanks in advance. Yours sincerely, S.Mahalakshmi [[alternative HTML version deleted]]

Hi, I am looking for a R package which is capable to process and analysis pictures of tissues (stained) in an automatic way. I had a look on biops and EBImage (Bioconductor) but they are not automatic... Did you already use/know a such package ? Thanks, - Martial _________________________________________________________________ Tchattez en direct en en vidéo avec vos amis !

Hi, I was wondering I'm going about this in the correct way. I need to test if there are coding sequences or exons in hg19 which match a string of 100bp "D" i.e. [A,G or T]. However I'm getting a strange result. I get a hit on chr7, using the 100bp search however when I search with 60bp sequence of "D" I don't get any hits. library("BSgenome")

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

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 Model 1 is the correct one

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 ~ tissue + gender +

Hi, I am very new to R and wanted to know if there is a package that, given very long nucleotide sequences, searches and identifies short (7-10nt) motifs.. I would like to look for enrichment of certain motifs in genomic sequences. I tried using MEME (not an R package, I know), but the online version only allows sequences up to MAX 60000 nucleotides, and that's too short for my needs..

Dear all, I would like to know if it is possible to fit in R a Cox ph model with time-dependent covariates and to account 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

Dear Ioannis Thank you very much for pointing me to meta-analysis. Although it may not solve my problem with the normalization, it gives me some other options to display the different correlation coefficients. One possibility is the use of Funnel plots, which are even available in library(rmeta). Another possibility is the use of forest-plots, as implemented in rmeta as metaplot. Sorrowly,

Hi, I've lost my mind on it... I have to scatterplot two vectors, grouped by a third variable, with two different dimensions according to whether each cell line in the plot is sensitive or resistant to a given drug, and with a different color for each of 9 tissues of origin. Here's what I've done:

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

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

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

I cannot find in the literature a way to conduct the following t.test on 2 objects, A and B A B col1 col2 col3 col1 col2 col3 Where col(i)'s name is identical in both A and B (they are names of tissues). How do I test (t.test) if each tissue across the object is signifanctly different?? (i'm pretty sure I have to use tapply())

Great R people, I have noticed a strange behaviour in read.delim() and friends in the R 2.7.0 version. I will describe you the problem and also the solution I already found, just to be sure it is an expected behaviour and also to tell people, who may experience the same difficulty, a way to overcome it. And also to see if it is a proper behaviour or maybe a correction is needed. Here is the