similar to: setting pairwise comparisons of columns (genes)

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

Hi, I am trying to test for pairwise associations between genotypes ( Rows=individuals, Columns =genes, data are up to 4 genotypes per gene, some with 2,3 or 4) where each chisquare comparison is different depending on the genes tested. The test is the observed multilocus (across columns for each individual) genotypes vs the expectation, which is the product of the individual frequency for each

I have several linear models on the same data: m1 <- lm(y ~ poly(x,1)) m2 <- lm(y ~ poly(x,2)) m3 <- lm(y ~ poly(x,3)) What I don't understand is why anova(m1, m2, m3, test="F") - yields the same RSS and SS values, but a different p-value from anova(m1, m2, test="F") - when it also yields the SAME as anova(m2, m3, test="F") What am I missing? Rob

Hi! I have been working several years with R but it's my first public question. I hope I'll be clear :) . This question is related to obtaining letter-based representation of non-parametric pairwise comparisons. I have a dataframe with this structure (but with quite more rows and cols): A B C factor 1 2 2 one 2 1 2 one 2 2 3 two 2 3 2 two 1 4 2 three 9 8 1 three I have no normality,

Hello, I have a linear model with different slopes for different treatment groups. I need to pairwise compare the different slope estimates for the different treatment groups. Is there a package that does pairwise comparisons of slope coefficients, making the appropriate adjustments in the P values? Thanks, John. -- ========================================== John Janmaat Department of

Hello R listing, I did two-way anova on lm. Further question the investigator interested in is what two treatments are different? I am looking for a command which could do pairwise comparison for every treatment. Could anyone help me out? Thanks a bunch Kevin

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

I'm interested in restricting the pairwise comparisons of interaction effects in a multi-way factorial ANOVA, because I find comparisons of interactions between all different variables different to interpret. For example (supposing a p<0.10 cutoff just to be able to use this example): > summary(fm1 <- aov(breaks ~ wool*tension, data = warpbreaks)) Df Sum Sq Mean Sq F

Hi, I've got this model and following Hothorn et al advices, I used glht for a post hoc comparison > modezqM<-glm(rojos~estacion*zona3,quasipoisson,subset=(edadysexo=="M")) > anova(modezqM,test="F") Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 293 41148

Also, this works (taking out multcomp=TRUE, multcompmethod="adjusted"): com.test=ma(Head.W1~Leg.3.1+Site, type="elevation", data=queens) print(com.test) ....so for some reason it will do an MA regression on all my data point together, but shows an error when I try to do pairwise comparisons between groups. Thank you, Ioulia -------- On Fri, May 11, 2012 at 2:09 AM, Ioulia

Hello, I have a unconventional question arising from my current master thesis on regression modeling. Suppose we have fitted a (linear) relationship between a dependent variable y and an independent variable x. Now we choose two points on the x-axis, i.e. according to percentiles x10 and x90. These two points are chosen to select the data points for two groups in order to perform pairwise

Hello, I am a new R user. I am trying to calculate vector correlations for all pairwise comparisons in my data frame without repeats. I am familiar with the expand.grid function, but this includes repeats. Is there a way to use expand.grid and eliminate repeats? Or is there another function that can be used to do this? Thank you. Rebecca -- Rebecca Young Graduate Student Ecology &

Hello, this is probably more a statistical question than an R-specific problem, but I'll risk it. I've fitted a Cox Proportional hazard model with one factor Treatment (seven levels) as a predictor variable. The general Null hypothesis (all groups show the same survival behaviour) is clearly rejected. Now, is there any (statistically sensible) way of doing pairwise comparisons and/or

# Hello # I have a question regarding pairwise calculations of a matrix using a "for-loop." # Below I have a matrix "X" with 8 columns. These are genotypic data so Column1 & Column2 is # a unit, Column3 & Column4 is a unit, Column5 & Column6 is a unit, and Coulmn7 & 8 is a unit. # I have a loop designed to calculate the number of times an individual in

Hi, I am simply looking for the function that will allow you to look at the top 20 lines of a long dataset? LP On Mon, Nov 1, 2010 at 10:46 AM, Louis Plough <lplough@usc.edu> wrote: > Hi, > I am trying to generate all possible permutations (choose 2) of a vector, > b, for example--using 'combn' the combinations in only one direction are > generated... > > >

Dear R users, I have the following two problems, related to the function sub, grep, regexpr and similia. The header of the file(s) I have to import is like this. c("y (m)", "BD (g/cm3)", "PR (Mpa)", "Ks (m/s)", "SP g./g.", "P (m3/m3)", "theta1 (g/g)", "theta2 (g/g)", "AWC (g/g)") To get rid of spaces and

Hi , I am new to R . I am facing difficulty how to make pairwise comparisions. For example. I have a file which looks like below a b c d x 3 6 7 6 y 7 8 6 5 z 5 4 7 8 Here I need to look for the each pairwise comparisions (ab,ac,ad,bc,bd,cd for each row) For instance ,looking at first row, for x i need to look for ab values and take the min(3,6) >5 ,if its satistfies the count should be

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

I'm able to do this as follows, but am wondering if anyone knows a simpler way which still avoids explicit loops? > (mystring <- letters[1:5]) [1] "a" "b" "c" "d" "e" > unlist(sapply(mystring[-length(mystring)], + function(x) paste(x,mystring[(grep(x,mystring)+1):length(mystring)],sep=""))) a1 a2 a3

I am familiar with pairwise t-tests, corrections for multiple testing, etc. however I have a problem whose answer I have not found after extensive R-help archive and Google searching. What I have done in the past: I have N items which are measured, exposed to a condition, and then measured again. I wish to know if the condition changes the items so I can perform a t-test. Better yet I can