similar to: Process File Line By Line Without Slurping into Object

Dear all, I have a repository file (let's call it repo.txt) that contain two columns like this: # tag value AAA 0.2 AAT 0.3 AAC 0.02 AAG 0.02 ATA 0.3 ATT 0.7 Given another query vector > qr <- c("AAC", "ATT") I would like to find the corresponding value for each query above, yielding: 0.02 0.7 However, I want to avoid slurping whole repo.txt

Dear all, For example I want to process set of files. Typically Perl's idiom would be: __BEGIN__ @files = glob("/mydir/*.txt"); foreach my $file (@files) { # process the file } __END__ What's the R's way to do that? - Gundala Viswanath Jakarta - Indonesia

Hi all, I have the following named list: > print(y) $`200052_s_at` [1] -1066.975 -1063.893 -1062.815 -1062.121 -1059.004 $`200071_at` [1] -959.823 -953.980 -953.886 -948.781 -974.890 $`200084_at` [1] -1135.804 -1132.863 -1128.197 -1128.633 -1125.890 What I want to do is to iterate this name list and process its members. To do that I attempt the following code (but failed): __BEGIN__ ny

Hi, Currently I have a density plot generated with this snippet. Is there a way I can add a line curve on top of it? I mean in one figure __BEGIN__ myhist <- hist(x col="blue", main = "Density Plot", xlab = "Exp Level", ) __END__ - Gundala Viswanath Jakarta - Indonesia

Hi, With the following codes, I attempt to convert the data.frame into a matrix. However I notice that data.matrix function doesn't seem to work. __ BEGIN__ dat <- read.table("mydata", comment.char = "!" , na.strings = "null"); # Select n-genes by random sample # n = 1 nosamp <- 1 geneid <- sequence(nrow(dat)) geneid.samp <- sample(geneid,nosamp)

Hi, How can I partitioned an example vector like this > print(myvector) [1] 30.9 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 into the following pairwise partition: PAIR1 part1 = 30.9 part2 = 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 PAIR2 part1 = 30.9 60.1 part2 = 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 .... PAIR9 part1 = 30.9

Dear all, I found that printing with 'cat' is very slow. For example in my machine this snippet __BEGIN__ # I need to resolve to use this type of loop. # because using write(), I need to create a matrix which # consumes so much memory. Note that "foo, bar, qux" object # is already very large (>2Gb) for ( s in 1:length(x) ) {

Hi, Suppose I have the following data frame. __BEGIN__ > library(MASS) > data(crabs) > crab.pca <- prcomp(crabs[,4:8],retx=TRUE) > crab.pca$rotation PC1 PC2 PC3 PC4 PC5 FL 0.2889810 0.3232500 -0.5071698 0.7342907 0.1248816 RW 0.1972824 0.8647159 0.4141356 -0.1483092 -0.1408623 CL 0.5993986 -0.1982263 -0.1753299 -0.1435941 -0.7416656 CW

Dear all, Does R has any function/package that can pack and unpack string into bit size? The reason I want to do this in R is that R has much more native statistical function than Perl. Yet the data I need to process is so large that it required me to compress it into smaller unit -> process it -> finally recover them back again into string with new information. In Perl the

Hi all, I have the following data in which I want to parse and store them in a list __DATA__ > print(comp.ll) [1] "\tGene 11340 211952_at RANBP5 k= 1 LL= -970.692 " [2] "\tGene 11340 211952_at RANBP5 k= 2 LL= -965.35 " [3] "\tGene 11340 211952_at RANBP5 k= 3 LL= -963.669 " [4] "\tGene 12682 213301_x_at TRIM24 k= 1 LL= -948.527 "

Hi, I have the following dataset (simplified for example). __DATA__ 300.35 200.25 104.30 22.00 31.12 89.99 444.50 22.10 43.00 22.10 200.55 66.77 Now from that I wish to do the following: 1. Compute variance of each row 2. Pick top-2 row with highest variance 3. Store those selected rows for further processing To achieve this, I tried to: a) read the table and compute variance for each row,

Dear experts, I tried to put the two plots into one final PNG figure with the following script. However instead of giving 2 plots in one figure, it only gives the the last plot in one figure. What's wrong with my script below? __BEGIN__ in_fname <- paste("mydata.txt.",sep="") out_fname <- paste("finalplot.png",sep="") dat <-

Hi, I have the following data frame: > print(mydatframe) __DATAFRAME__ V1 V2 V3 1 1007_s_at DDR1 discoidin domain receptor tyrosine kinase 1 2 1053_at RFC2 replication factor C (activator 1) 2, 40kDa 3 117_at HSPA6 heat shock 70kDa protein 6 (HSP70B') __END__ Is there a way to create a hash with V2 as Key and V3 as its value? - Gundala Viswanath Jakarta - Indonesia

Hi all, After running this code (attaches is the input file): dat <- read.table("gene_prob.txt", sep = "\t") n <- length(dat$V1) print(n) print(dat$V1) I get this print out. ...... [8541] LOC552889 GPR15 SLC2A11 GRIP2 SGEF [8546] PIK3IP1 RPS27 AQP7 8548 Levels: 3.8-1 A2M A4GALT A4GNT AAAS AAK1 AAMP AANAT AARSD1 AASS ...

Hi all, I have a function - let's call it "myfunction". This function is based on some random number generator. Now, once in a while the function will break/crash depending on the random number it generate inside the function. To avoid the problem, what I intend to do is the following: 1. Catch the try-error using class. 2. Redo the function if it returns "try-error" 3.

Hi, I have the following data file to be parsed and captured as a data frame: __DATA__ #GDS_ID GENE_NAME GENE_DESCRIPTION GENE_FUNCTION 1007_s_at | DDR1 | discoidin domain receptor tyrosine kinase 1 | protein-coding 1053_at | RFC2 | replication factor C (activator 1) 2, 40kDa | protein-coding 117_at | HSPA6 | heat shock 70kDa protein 6 (HSP70B') | protein-coding __END__ In particular it is

Hi all, I've tried to plot a vector which has two peaks in the density. This link shows the figure. http://docs.google.com/View?docid=dcvdrfrh_1dk9r2rc7 The red line is normal curve and green line is gamma curve. Notice that red line can correctly fit the histogram that has two peaks (i.e. red curve also has two peaks). But the gamma curve there only has one curve. Is there a way I can

Dear all, I have the following code that try to plot simple sinus curve into 2x2 grid in 1 page. But this code of mine create 4 plots in 1 page each. What's wrong with my approach? __BEGIN__ library(lattice) library(grid) test.plot <- function(x,y) { pushViewport(viewport(layout.pos.col=x, layout.pos.row=y)) pushViewport(viewport(width=0.6, height=0.6)); plot(sin,-pi,2*pi, main=

I have a data which contain some NA value in their elements. What I want to do is to **perform clustering without removing rows** where the NA is present. I understand that `gower` distance measure in `daisy` allow such situation. But why my code below doesn't work? __BEGIN__ # plot heat map with dendogram together. library("gplots") library("cluster")

Hi Dieter, Sorry my mistake. I wanted to convert them into Decimal (not Hexadecimal). Given this string, the desired answer follows: > ascii_str <- "ORQ>IK" 79 82 81 62 73 75 > ascii_str2 <- "FDC" 70 68 67 - Gundala Viswanath Jakarta - Indonesia On Mon, Dec 22, 2008 at 5:49 PM, Dieter Menne <dieter.menne at menne-biomed.de> wrote: > Gundala