similar to: "CV" for log normal data

Hello guys! I am working with some classifiers ( SVM,C4.5,RNA,etc) using 10-C.V. Once I have the model of each one, I make the validation of these models in one dataset. Then,with my model and the dataset, I extract a confusion matrix to know the capacity of prediction from the model. And finally, I extract the accuracy of this prediction based on the diagonal from the confusion matrix. The

The function knn.cv in the class package doesn't have error checking to ensure that the length of the classlabel argument is equal to the number of rows in the test set. If the classlabel is short, the result is often a segfault. > library(class) > dat <- matrix(rnorm(1000), nrow=10) > cl <- c(rep(1,5), rep(2,5)) > cl2 <- c(rep(1,5), rep(2,4)) > knn.cv(dat, cl) [1] 2

How can I subscribe to R genomic list? On Sun, 2 Apr 2023, 9:28 pm Peter Langfelder, <peter.langfelder at gmail.com> wrote: > It's a microarray data set, so I don't think you would want to apply > an RNA-seq pipeline. You'd be better off applying a normalization > appropriate for this type of microarray data. > > HTH, > > Peter > > On Sun, Apr 2, 2023

It's a microarray data set, so I don't think you would want to apply an RNA-seq pipeline. You'd be better off applying a normalization appropriate for this type of microarray data. HTH, Peter On Sun, Apr 2, 2023 at 11:09?PM Anas Jamshed <anasjamshed1994 at gmail.com> wrote: > > I want to get the count matrix of genes from >

I have a very basic question about limma. Assume I have experiments from 3 or more RNA sources in a reference design. It is easy to define individual contrasts but I want to specify a contrast matrix that tests for significant differences among ALL the different RNA sources (i.e. the analogous thing to a simple One-Way ANOVA). How can I do that? Thanks! Max --

I want to get the count matrix of genes from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146049. Is it possible for GSE146049? After getting counts, I want to do TMM normalization. [[alternative HTML version deleted]]

Dear all, I have a question about limmaGUI that is usually run in R environment. My problem is loading data into the programm. I have 6 gpr files that apparently are not compatible with limma. Everytime I'm trying to load the data (including a RNA targets file, an error appears:Error reading files. that I'm not sure,but seems to have something to do with the format of my files

Hi, I am performing Cox proportional hazards regression on a microarray dataset with 15000 genes. The p values generated from the Cox regression (based on normal distribution of large sample theory) showed only 2 genes have a p value less than 0.05. However, when I did a permutation on the dataset to obtained permutated p values, and it turned out about 750 genes had a permutated p value less than

Hi, I am following the protocol outlined here for analysis of single channel Agilent microarray data: http://matticklab.com/index.php?title=Single_channel_analysis_of_Agilent_microarray_data_with_Limma I keep getting the following error message when using Limma's read.maimages function to load my data into an RGList object: Error in RG[[a]][, i] <- obj[, columns[[a]]] : number of

Hi there, I am trying to use predict() with an object returned by cv.glmnet(), and get the following error: no applicable method for 'predict' applied to an object of class "cv.glmnet" What's wrong? my code: x=matrix(rnorm(100*20),100,20) y=rnorm(100) cv.fit=cv.glmnet(x,y) predict(cv.fit,newx=x[1:5,]) coef(cv.fit) Thanks so much, Asaf -- View this message in context:

Dear all, not really a R question but: If I want to check for the classification accuracy of a LDA with previous PCA for dimensionality reduction by means of the LOOCV method: Is it ok to do the PCA on the WHOLE dataset ONCE and then run the LDA with the CV option set to TRUE (runs LOOCV) -- OR-- do I need - to compute for each 'test-bag' (the n-1 observations) a PCA

Hi, perhaps you can help me to find out, how to find the best Lambda in a LASSO-model. I have a feature selection problem with 150 proteins potentially predicting Cancer or Noncancer. With a lasso model fit.glm <- glmpath(x=as.matrix(X), y=target, family="binomial") (target is 0, 1 <- Cancer non cancer, X the proteins, numerical in expression), I get following path (PICTURE

Hi, I've done some searching where others have had trouble with this error (or "warning" actually), but I'm unable to solve my problem. I have a data sheet with 13 columns and 36 rows. Each column has exactly the same number of rows. I've created glms and now want to do cross-validation on 2 of them. Please be gentle-- I'm new to R (and statistics, too, for that

Dear R-Helpers, I am trying to bootstrap the coefficient of variation on a suite of vectors, here I provide an example using one of the vectors in my study. When I ran this script with the vector x <-c(0.625, 0.071428571, 0.133333333, 0.125, 0), it returned CV(boot) [the second one], and stderr(boot) [the second one] without problem. However, when I ran it with the vector in the

Hi, Newbie question about the pls package. Setup: Mac OS 10.3.9 R: Aqua GUI 1.01, v 2.0.1 I want to get R^2 and Q^2 (LOO and Leave-10-Out) values for each component for my model. I was running into a few problems so I played with the example a little and the results do not match up with the comments in the help pages. $ library(pls) $ data(NIR) $ testing.plsNOCV <- plsr(y ~ X, 6, data =

Hi everyone, I'm trying to generate an RNA degradation plot of the Estrogen example data plot, but seem to get an error. I've tried defining an ylim value, ylim=c(0,30) , but it doesn't seem to work either. My code is as follows: > RNAdeg<-AffyRNAdeg(Data) > png(DegLoc, width=720, height=720) > par(ann=FALSE) > par(mar=c(3,3,0.1,0.1)) >

Dear all, I've tried a multiple regression, and now I want to try a cross-validation. I obtain this error (it must be sth related to df) that I don't understand, any help would be appreciated. cv.lm(df= dat, lm2.52f, m=3) Error en `[.data.frame`(df, , ynam) : undefined columns selected lm2.52f is my lm object, dat is a dataframe where the variables involved in .lm are I tried CVlm

Hi I am using clang-6 to compile this C++ code and I see a strange temporary variable allocated at expression address 0x7ff1131536e8. If I change the ternary operator at line 483 to an if-else, the temporary is not allocated. Thanks Variables: ========= FFMPEGVideoCapture ffmpeg_video_capture_; cv::VideoCapture opencv_video_capture_; Function: ======== bool

Dear list, I am modelling fish distributions using the glm-function followed by the step-function, and then want to cross-validate the model via the cv.glm-function from the {boot} package. I am working on fish distributions on coral reefs. The code I have works for one fish species. Since I have 227 fishes, I wrote a loop. Now the cv.glm-function comes up with an error message: "Error in

I'm working with a very large matrix ( 22k rows x 2k cols) of RNA expression data with R v.2.5.0 on a RedHat Enterprise machine, x86_64 architecture. The relevant code is below, but I call a function that takes a cluster of this data ( a list structure that contains a $rows elt which lists the rows (genes ) in the cluster by ID, but not the actual data itself ). The