similar to: Fw: Help with loops(corrected question)

Hi I am trying to create a loop which averages replicates in my data. The original data has many rows. and consists of 40 column zz[,2:41] plus row headings in zz[,1] I am trying to average each set of values (i.e. zz[1,2:3] averaged and placed in average_value[1,2] and so on. below is my script but it seems to be stuck in an endless loop Any suggestions?? for (i in 1:length(average_value[,1])) {

Hi i am using a script which involves the following loop. It attempts to reduce a data frame(zz) of 95000 * 41 down to a data frame (averagedreplicates) of 95000 * 21 by averaging the replicate values as you can see in the script below. This script however is very slow (2days). Any suggestions to speed it up. NB I have also tried using rowMeans rather than adding the 2 values and dividing by 2.

Hello R-users, I am looking for an elegant way to calculate p-values for each row of a data frame. My situation is as follows: I have a gene expression results from a microarray with 64 samples looking at 25626 genes. The results are in a data frame with the dimensions 64 by 25626 I want to create a volcano plot of difference of means vs. ?log(10) of the p-values, comparing normal samples to

Hi R-users, I have missing data for the month. My question is how do I insert the missing month and fill up the cell with 'na' for the rain amount?  Then I would like to count the percentage of missing data. No     Year     month rain 1398 1985    10 104.2 1399 1985    11 138.0 1400 1985    12 120.4 1401 1986     1  12.6 1402 1986     2  19.4 1403 1986     3   1.0 1404 1986     4  58.8

I think I understand tapply but i still can't figure out how to do the following. I have a dataframe where some of the column names are the same and i want to make a new dataframe where columns that have the same name are averaged by row. so, if the data frame, DF, was AAA BBB CCC AAA DDD 1 0 7 11 13 2 0 8 12 14 3 0 6 0 15

Hi, May be this helps: ?set.seed(24) ?mydata4<- as.data.frame(matrix(sample(1:100,10*38,replace=TRUE),ncol=38)) ?dim(mydata4) #[1] 10 38 ?library(matrixStats) res<-do.call(cbind,lapply(1:400, function(i) {permutation<-sample(mydata4); (rowMeans(permutation[,1:27])-rowMeans(permutation[,28:38]))/(rowSds(permutation[,1:27])+rowSds(permutation[,28:38]))} )) ?dim(res) #[1]? 10 400 A.K.

Hello, I am trying to create parcels for a CFA model. I am trying to average 6 sets of 3 variables each into parcels. I don't understand why I am getting an error message as follows: Thanks for your help, Catherine atds1par <- rowMeans(semHW1dat1[, c("atds1", "atds2", "atds3")], na.rm=TRUE) atds2par <- rowMeans(semHW1dat1[, c("atds4",

How do we specify a contrast interaction matrix for an ANOVA model? We have a two-factor, repeated measures design, with Cue Direction (2) x Brain Hemisphere(2) Each of these has 2 levels, 'left' and 'right', so it's a simple 2x2 design matrix. We have 8 subjects in each cell (a balanced design) and we want to specify the interaction contrast so that: CueLeft>CueRght

Hello! I have a dataset like this: X1 X2 X3 X4 X5 X6 X7 X8 1 2 2 1 2 3 2 6 2 3 2 5 7 9 1 3 1 9 12 6 1 1 3 6 The columns X1-X6 contains ordinary numeric values. X7 contains the number of the first column that the rowMeans should be calculated from and X8 contains the last column

Dear List, I'm not even sure this is an issue or not, but ?rowMeans has: Value: A numeric or complex array of suitable size, or a vector if the result is one-dimensional. The ?dimnames? (or ?names? for a vector result) are taken from the original array. If there are no values in a range to be summed over (after removing missing values with ?na.rm = TRUE?), that

Hi all, I have a matrix called 'data', which looks like: > data[1:4,1:4] Probe_ID Gene_Symbol M1601 M1602 1 A_23_P105862 13CDNA73 -1.6 0.16 2 A_23_P76435 15E1.2 0.18 0.59 3 A_24_P402115 15E1.2 1.63 -0.62 4 A_32_P227764 15E1.2 -0.76 -0.42 > dim(data) [1]

I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation: Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T)

Hello, I have some dataset, which i read it from external file using the (data <- read.csv("my file location")) and read as a dataframe > is(data) [1] "data.frame" "list" "oldClass" "vector" but i have also converted this into a matrix and tried to apply my code but didnt work. Anyways, suppose i have the following data.

In R 3.3.3, I observe the following on Ubuntu 16.04 (when building from source as well as for the sudo apt r-base build): > x <- c(NA, NaN) > mean(x) [1] NA > mean(rev(x)) [1] NaN > rowMeans(matrix(x, nrow = 1, ncol = 2)) [1] NA > rowMeans(matrix(rev(x), nrow = 1, ncol = 2)) [1] NaN > .rowMeans(x, m = 1, n = 2) [1] NA > .rowMeans(rev(x), m = 1, n = 2) [1] NaN >

Hi I am using the following script to average a set of data 0f 62 columns into 31 colums. The data consists of values of ln(0.01) or -4.60517 instead of NA's. These need to be averaged for each row (i.e 2 values being averaged). What I would I need to change for me to meet the conditions: 1. If each run of the sample has a value, the average is given 2. If only one run of the sample has a

Hello: I'm reading in a series of text files (100 files that are each 2000 rows by 6 columns). I wish to combine the columns (6) of each file (100) and get the row mean. I'd like to end up with a data.frame of 2000 rows by 6 columns. foo <- list() for(i in 1:10){ # The real data are read in from a series of numbered text files foo[[i]] <- data.frame(x1 = rnorm(100), x2 =

Hello, I'm having trouble in using "assign(paste ..." command . I could create several dataframes following trinomial distribution using it but it could not be used to check their row means of the created dataframe. For example, the following works: probTrt=matrix(0,4,3); probTrt; #malf, death, normal probTrt[1,]=c(0.064,0.119,0.817);#for Trt 1 probTrt[2,]=c(0.053,0.125,0.823);#for

Dear readers of the list, I have a problem a comparison of two data from a vector. The comparison yields FALSE but should be TRUE. I have checked for mode(), length() and attributes(). See the following code (R2.10.0): ----------------------------------------------- # data vector of 66 double data X =

On Fri, Mar 31, 2017 at 10:14 PM, Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote: > From ?NA > > Numerical computations using ?NA? will normally result in ?NA?: a > possible exception is where ?NaN? is also involved, in which case > either might result. > > and ?NaN > > Computations involving ?NaN? will return ?NaN? or perhaps ?NA?: >

Hi, I am a Ph.D. student from Québec, Canada. I’m a beginner with R and Bioconductor. Until now the only experience I have is in analyzing microarray data using affy and limma packages. Now I am trying to analyze Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth moderated t test on those arrays. Since no cdf official package is available for those arrays, after reading many