similar to: stats and generating a figure for a simple sign test with high inter-experiment variance

Hello all, Sorry if this is an FAQ. I have been trying to search the archives without success. I have a dataset (ChiPs microarray) where the experiment to experiment variability is very high but where within an experiment, the data nearly always goes in the "right" (hypothesis confirming) direction. I am trying to figure out the right way to use R to do the statistical analysis and

Hello, Apologies if this is the wrong list, I am a first-time poster here. I have an experiment in which an output is measured in response to 42 different categories. I am only interested which of the categories is significantly different from a reference category. Here is the summary of the results: summary(simple.fit) Call: lm(formula = as.numeric(as.vector(TNFa)) ~ Mutant.ID, data =

Jenner lab, University College London Our laboratory uses genomics and biochemical techniques to identify how transcription factors, chromatin modifiers and non-coding RNAs act to regulate cell differentiation. Our research has led to the characterisation of a class of short RNAs transcribed from polycomb target genes that interact with polycomb repressive complex-2 (Kanhere et al., Mol Cell

Version of R: Windows Version 2.0.0 The experimental design contains two plant lines - a control (C) and a mutant (M) - grown out three separate times in plots A, B, C. The design is unbalanced: In plot A, 9 control plants were grown with 29 mutant plants. In plot B, 8 control plants were grown with 20 mutant plants. In plot C, 8 control plants were grown with 22 mutant plants. The

Hello, everybody. We are working on a tool for mutation testing. The work is still in progress and far away from being done. However, we have got some results already. And we would like to share them with you. But, let me give you a brief introduction first. ### Mutation Testing In a nutshell, Mutation Testing is a way to evaluate a quality of a test suite. The approach suggests introducing a

Hello All, This will probably be easy for some but isn't for me. Currently am working on a text mining exercise. Want to be able to predict whether cancer patients got KRAS testing, and, if so, whether the test yielded a result of wild type/negative or mutant/positive. I've begun with a "bag-of-words approach" that looks at the count of specific terms in the medical records and

Hello All, Started out awhile ago trying to select columns in a dataframe whose names contain some variation of the word "mutant" using code like: names(KRASyn)[grep("muta", names(KRASyn))] The idea then would be to add together the various columns using code like: KRASyn$Mutant_comb <- rowSums(KRASyn[grep("muta", names(KRASyn))]) What I discovered though, is

Hey Paul, Thanks for the reply! If you wanted you could try my radio stream, http://stream.socorock.com:8000/socorock.ogg.m3u - that's really good news, I think I'm gonna pick up one of these things soon! What a great way to listen to radio. Cheers, Jordan On 02/26/2012 12:01 AM, Paul Webster wrote: > The Grace and Logitech devices can play streaming OGG. I have different models of

Hi, I have a data set like this: Mutant Rep Time OD 02H02 1 0 0.029 02H02 2 0 0.029 02H02 3 0 0.023 02H02 1 8 0.655 02H02 2 8 0.615 02H02 3 8 0.557 02H02 1 12 1.776 02H02 2 12 1.859 02H02 3 12 1.668 02H02 1 16 3.379 02H02 2 16 3.726 02H02 3 16 3.367 306 1 0 0.033 306 2

Hi All, I wonder if there should be one character for quote= in read.table, i.e., > args(read.table) function (file, header = FALSE, sep = "", quote = "\"'", dec = ".", ... I have a file containing the following lines, 08248-GOTERM 3'-phosphoadenosine 5'-phosphosulfate biosynthetic process 08279-GOTERM 3'-phosphoadenosine

Hello Everyone, I have what I think is a complex text parsing task. I've provided some sample data below. There's a relatively simple version of the coding that needs to be done and a more complex version. If someone could help me out with either version, I'd greatly appreciate it. Here are my sample data. haveData <- structure(list(profile_key = structure(c(1L, 1L, 2L, 2L, 2L,

Hi all, I'm working on microarray and currently analyzing the microrarray data using limmaGUI. Loop design has been applied in this experiment. This is a 2X2 factorial experiment where there are control and treatment at 2 different time points, week 6 and 9. The experimental design is almost the same as the limmaGUI work example: Weaver Data set. I would like to look at the effect of

Dear list, I wish to plot chromatin precipitation data: I would like to have a rectangles (x:end-start, y:peak) but I do not have an idea how to define x (in terms of qplot syntax) and to choose the correct geom. mydata is a subset of a larger file. > mydata chrom start end peak 1 chr11 5291000 5291926 8 2 chr11 10988025 10988526 7 3 chr11 11767950 11768676 8 4

Hello all, I am getting into trouble when trying to do standard I/O from a C function called within R environment. This function is written in a small C library that is loaded whith dyn.load() and called in R via the .C() interface. I need to debug the C code using a text file for some logs, and also to speed up its result visualization by creating images on the fly using the GD library. Both

Hello, In limmaGUI, after running a linear model for a single gene & time point (mutant vs control), the venn-diagram for differentially expressed genes with a p-value cut-off gives a different number than the top-table with the same cut-off (2600 vs. 791). I have seen the same thing happen before for multiple time points (when the venn-diagram is more relevant) Any ideas what is going on?

On 04.06.2017 11:50, jing hua zhao wrote: > Hi All, > > > I wonder if there should be one character for quote= in read.table, i.e., > > >> args(read.table) > function (file, header = FALSE, sep = "", quote = "\"'", dec = ".", > ... > > I have a file containing the following lines, > > > 08248-GOTERM

I knew it couldn''t possibly go right. First attempt at upgrading a 0.1.0 host trashed the networking config majorly. In defense of 0.1.1, I did have an odd networking config (since XCP had problems with the built in Broadcom ports, I pif-forgetted them and let Linux handle them. If it weren''t for the mutant network config, I bet 0.1.1 would have done ok. More seriously,

HI everyone, I'm plotting a histogram in R and within that histogram i need to demonstrate the percentage of another variable (Percentage of MutStatus) within the bins plotted inthe histogram....I don't know how to do that! Data:Validation_Status Mutation_Status TvarRatio Wildtype None 0.08 Wildtype None 0.08 Wildtype None 0.08 Wildtype None 0.08 Wildtype None 0.080139373 Wildtype None

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Hello, R experts, I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below: score<-c(7.2,6.5,6.9,6.4,6.9,6.1,6.9,5.3,7.2,5.7,5.1,5.9,7.6,6.9,6.8,