similar to: clustering genes / automatically determining # of clusters

Hi: I'm clustering a microarray dataset with a large # of samples. I would like your opinion on the best way to automatically determine the optimal # of clusters. Currently I am using the "cluster" package, clustering with "clara", examining the average silhouette width at various numbers of clusters. I'd like opinions on whether any newer packages offer

After ordering the table of membership degrees , i must get the difference between the first and second coloumns , between the first and second largest membership degree of object i. This for K=2,K=3,....to K.max=6. This difference is multiplyed by the Crisp silhouette index vector (si). Too it dependending on K=2,...,K.max=6; the result divided by the sum of these differences I need a final

Hello R-listers, I'm having trouble accessing "sub" objects ("attributes"?), e.g., "x$silinfo$avg.width" using the /get() /command; I'm using/ get()/ in a loop as illustrated in the following code: #FIRST MAKE CLUSTERS of VARYING k /for (i in 1:300){ assign(paste("x.",i,sep=""),pam(x,i)) #WORKS FINE }/ #NEXT, TAKE LOOK AT AVE.

Dear all, I got this error message > library(dprep) > mardia(Savg) Error in cov(data) : 'x' is empty But with the same data, I got > library(mvnormtest) > mshapiro.test(Savg) Shapiro-Wilk normality test data: Z W = 0.9411, p-value = 0.6739 What does the error message "Error in cov(data) : 'x' is empty" mean? Thanks a lot! Jiao

HI R users With clara function I get a data frame (maybe this is not the exact word, I'm new to R) with the following variables: > names(myclara) [1] "sample" "medoids" "i.med" "clustering" "objective" [6] "clusinfo" "diss" "call" "silinfo" "data" I want to

Hi All, For the function "bclust"(e1071), the argument "base.method" is explained as "must be the name of a partitioning cluster function returning a list with the same components as the return value of 'kmeans'. In my understanding, there are three partitioning cluster functions in R, which are "clara, pam, fanny". Then I check each of them to

I am using some functions from package clusterSim to evaluate the best clusters layout. Here is the features vector I am using to cluater 12 signals: > alpha.vec [1] 0.8540039 0.8558350 0.8006592 0.8066406 0.8322754 0.8991699 0.8212891 [8] 0.8815918 0.9050293 0.9174194 0.8613281 0.8425293 In the following I pasted an excerpt of my program:

Hello R-Helpers, I have a question about extracting the clusters of genes after we make the heatmap (say ht4) using the heatmap.2 function. Basically, I want to get the clusters which are shown as row dendrogram in the heatmap. I understand that ht4$rowDendrogram is an object of dendrogram and it containes details of all the nodes and branches, but lets say I want to know the number of clusters

Hi, I'm having an issue with busy detection, the busy is not being detected. Asterisk: 1.6.2.13 DAHDI: 2.4.0 Chandahdi: busydetect=yes, busycount=2 Indications zone = us, with the modifications for my country for busy: 425Hz Pattern(0.2ms on, 0.2ms off, 0.2ms on, 0.6ms off) I compiled with BUSY DETECT DEBUG. I can see: [Feb 10 15:48:06] DEBUG[26968]: dsp.c:1276

hello, i'm pete ,how can i order rows of matrix by max to min value? I have a matrix of membership degrees, with 82 (i) rows and K coloumns, K are clusters. I need first and second largest elements of the i-th row. for example 1 0.66 0.04 0.01 0.30 2 0.02 0.89 0.09 0.00 3 0.06 0.92 0.01 0.01 4 0.07 0.71 0.21 0.01 5 0.10 0.85 0.04 0.01 6 0.91 0.04 0.02 0.02 7 0.00 0.01 0.98 0.00 8 0.02

I'm doing prediction of the survival cases using gene expression profiles(Affymetrix chips). Can somebody tell me how to use the Cox PH model to select genes and make a prediction of survival? Thanks. Guangchun

Hi, recently, I got a bunch of DNA sequences (with chromosome coordinate for each sequence), I would like to know the relative distance between these sequences and all the genes (genomic sequences) on human genome, i.e., are these sequences locate at upstream of the genes(5 prime end), downstream of the genes(3 prime end) or within the genes. I have about 8000 sequences. Any package, methods

Hi, I have a number of genes (columns) for which I want to examine pairwise associations of genotypes (each row is an individual)...For example (see data below), I would like to compare M1 to M2, M2 to M3, and M1 to M3 (i.e. does ac from M1 tend to be found with bc from M2 more often than expected.) Down stream I will be performing chi square tests for each pair. But I am looking for a way to

Dear All: I have a question on using coxph for multiple genes: I have written code to loop through all 22283 genes in the Hgu-133A and apply coxph on survival data. However, I don't know how to work with the result for each gene: survtest<-coxph(Surv(pcc.primary.stg.3.cox[,'fup_interval'],pcc.primary.stg.

Hi, all, Anyone has experience on Logistf package? I am using logistftest in Logistf package to selelct diagnosis genes. The result seems not the same as I expected. I have 10 gene expression data for 27 tumor 1 and 11 tumor 0. I want to select the best one using Maximum likelihood ratio test in logistic regression model. This is the way my code works: 1. Read in 10 genes as independent

Hi Everyone, I am trying to find a way to do this in excel to tell me which genes are the most differentially expressed. Sorry, i couldn't find excel forum section in nabble. However, if it is in R it is fine. This is a microarray data, and it has been normalized. According to Dov Stekel in Microarray, i will need to calculate log ratio (control-treatment). Once you have the log ratio,

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

Hi, here's my siggenes.table$genes.up snippet. Two class unpaired SAMR analysis. "Row" "Gene ID" "Gene Name" "Score(d)" "Numerator(r)" "Denominator(s+s0)" "Fold Change" "q-value(%)" "1" "25" "RPL15P22" "RPL15P22" "-1.44115338424578" "-18"

Hi! I would like to select probes (affy expression set) of genes that are "cancer-related". Conventionally the decision whether a gene is cancer-related or not is made by looking up the literature. Since this is not possible for all genes on the array I wonder if there is a way of doing this automatically? Best wishes Kristian -- _____ Dr Kristian Unger Imperial College London

Hi I have a problem for which I would like to know a solution. I have a gene expression data and I would like to choose only lets say top 200 genes that had the highest expression variance across patients. How do i do this in R? I tried x=apply(leukemiadata,1,var) x1=x[order(-1*x)] but the problem here is x and x1 are numeric data , If I choose the first 200 after sorting in descending, so I