similar to: Error in inherits(x, "data.frame") : subscript out of bounds

Hello, I will be very obliged if someone can help me with this statistical R problem: I am trying to do a Pearson correlation on my datasets X, Y with randomization test. My X and Y datasets are pairs. 1. I want to randomize (rearrange) only my X dataset per row ,while keeping the my Y dataset as it is. 2. Then Calculate the correlation for this pair, and compare it to your true

Hi all, I want to get results for cox proportional hazards on SNP data. I'm trying to get HRs, CI's, & p-values for each individual SNP - this is represented by cov[,i]. When I run my code, I get the following error: subscript out of bounds. I don't know why I am getting this error. I have looked through the R logs, but nothing that has been previously suggested has helped so

Hi Group, Consider a data frame like this: mylabel1 <- rep(c("A","B","C"),each=3) mylabel2 <- rep(c("A","B","C"),3) corrs <- c(1,.8,.7,.8,1,.7,.7,.7,1) myData <- data.frame(mylabel1,mylabel2,corrs) myData mylabel1 mylabel2 corrs 1 A A 1.0 2 A B 0.8 3 A C 0.7 4 B

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On Wed, 4 Jun 2014, Katja Wegner wrote: > Date: Wed, 4 Jun 2014 16:21:04 +0200 > From: Katja Wegner <katja.wegner92 at web.de> > To: dovecot at dovecot.org > Subject: [Dovecot] IMAP copy fails because the mailbox size of user1 is > exceeding the quota limit of user2?? > > Hi all, > I do have a mailbox-quota problem

On 9 Aug 2018, at 10:09, Katja Abramova <katja.abramova at dimension.it> wrote: > I need to do a search for a > multi-word query in which particular fields are boosted - preferably at > query time. That is, given a query like "the cat is lying on the mat" (with > an OR operator, ignoring word positions but with stemming and stop words > removed), I'd like to

Hello everyone, is there a package/packages for factor analysis, particularly PCA? thanks, Katja Katja L??ytynoja Taitoniekantie 9 A 218 40 740 Jyv??skyl?? Finland tel.+35814 608058 cell.+35850 336 0174 kaloytyn at jyu.fi

Hello, I have a large data set 320.000 rows and 1000 columns. All the data has the values 0,1,2. I wrote a script to remove all the rows with more than 46 missing values. This works perfect on a smaller dataset. But the problem arises when I try to run it on the larger data set I get an error “cannot allocate vector size 1240 kb”. I’ve searched through previous posts and found out that it might

I have a 2 x 3 matrix called snp and I want to compute the following probability: choose(sum(snp[,1]), snp[1,1]) * choose(sum(snp[,2]), snp[1,2]) * choose(sum(snp[,3]), snp[1,3])/choose(sum(snp), sum(snp[1,])) but I keep getting Infs and NaNs. Is there a function that can do this in R? -- Thanks, Jim. [[alternative HTML version deleted]]

Hi, I am new to R. and even though I've made my code to run and do what it needs to . It is taking forever and I can't use it like this. I was wondering if you could help me find ways to fix the code to run faster. Here are my codes.. the data set is a bunch of 0s and 1s in a data.frame. What I am doing is this. I pick a column and make up a new column Y with values associated with that

Hi, I cant understand where I am going wrong.Below is my code.I would really appreciate your help. Thanks. > genfile<-read.table("c:/tina/phd/bs871/hw/genfile.txt",skip=1) > > #read in SNP data > snp.dat <- as.matrix(genfile) > snp.name <- scan("c:/tina/phd/bs871/hw/genfile.txt",nline=1,what="character") Read 100 items

Dear R experts, I have 2 matix: A& B. I am trying to index B against A - (1) find out B rows that fall between the col 1 and 2 of A& put them into a new vector SNP.I made code as below, but I cannot think of a right way to do it. Could anyone help me with the code? Thanks,Jiang---- A <-

Dear R colleagues, I annotated a list of single nuclotide polymorphiosms (SNP) with the corresponding genes using biomaRt. The result is the following data.frame (pasted from R): snp ensembl_gene_id 1 rs8032583 2 rs1071600 ENSG00000101605 3 rs13406898 ENSG00000167165 4 rs7030479

Hi I listened to all your advise and ran my data on a computer with a 64 bits procesor but i still get the same error saying "it cannot allocate a vector of that size 1240 kb" . I don't want to cut my data in smaller pieces because we are looking at interaction. So are there any other options for me to try out or should i wait for the development of more advanced computers!

Hi, I'm trying to melt() some data for subsequent cast()ing and am encoutering errors. The overall process requires a couple of casts()s and melt()s. ########Start Session 1########## ## I have the data in a (fully) melted format and can cast it fine... > norm1[1:10,] Pool SNP Sample.Name variable value 1 1 rs1045485 CA0092 Height.1 0.003488853 2 1 rs1045485

Hi, Following my earlier posts about having problems performing a PCA, I have worked out what the problem is. The problem lies within the PLINK to gds conversion. It seems as though the SNPs are imported as "samples" and in turn, the samples are recognised as SNPs: >snpsgdsSummary("chr2L") Some values of snp.position are invalid (should be > 0)! Some values of

Dear R users, I have some problems with the parLapply function from the "parallel" package: I use parLapply on a pretty big R object without changing the object within the called function. If I execute parLapply alone, everything works fine. It seems that the object resides only once in the memory. But if I use the same call within another function, the object seems to be multiplied to

Hi, I have a vector with elements rs.id=c(''rs100'',''rs101'',''rs102'',''rs103'') And a dataframe ''snp.id'' 1 SNP_100 rs100 2 SNP_101 rs101 3 SNP_102 rs102 4 SNP_103 rs103 Task is to replace

Hi, I am trying to match the order of the rownames of a dataframe with the rownames of another dataframe (I can't simply sort both sets because I would have to change the order of many other connected datasets if I did that): Also, the second dataset (snp.matrix$fam) is a snp matrix slot: so for example: data_one: x y

Dear All, I have a large data frame with 10 rows and 82 columns. I want to apply the same function to all of the columns with a single command. e.g. zl <- lm (snp$a_109909 ~ snp$lat) will fit a linear model to the values in lat and a_109909. What I want to do is fit linear models for the values in each column against lat. I tried doing zl <- (snp[,2:82] ~ snp$lat[,1]) but got the following

You could assign a density value to each point. Maybe you've done that already...? Then trim the lowest n (number of) data points Or trim the lowest p (proportion of) data points. e.g. Remove the data points with the 20 lowest density values. Or remove the data points with the lowest 5% of density values. I'll let you decide whether that is a good idea or a bad idea. And if it's a