similar to: GWA plot

Hello, I am trying to create a simple Manhattan plot for a small list of 200 SNPs spread out in the genome in different genes. I have tried different functions (using ggplot2 and a function created by Stephen Turner, mhtplot etc.)-none of them work smoothly. Does anyone have a simple way to create the plot (not for all 22 chromosomes)- with the x axis showing the genes name and not the

Hi, I'm trying to make a chromosomal map in R by using the locus. I have a list of genes and their locus, and I want to visualise that so you can see if there are multiple genes on a specific place on a chromosome. A example of what I more or less want is below: http://www.nabble.com/file/p21474206/untitled.JPG untitled.JPG The genes and locus are here:

Hi, I would like some extra information on the 'cgh' package in R. I noticed that there isn't much activity regarding this package on the R and BioC mailing list (I googled it). I started using this package and I have few questions: 1/ As I have a custom tiling like array @8um features resolution (affy), I have a lot of probes to work with. I'm assuming it is correct to

I'm new to R and struggling to reproduce graphs I've made with gnuplot. Example here: http://www.slamb.org/tmp/one-active.png I have three different data sets plotted on the same axis. (I also have a number of samples for each X value which I displayed with quartiles rather than plotting every point; that will likely be the subject of my next question.) My attempts to do this in R:

I'm trying to identify the positions of all genes within a specific chromosomal region using biomart. When using the current biomart database I'm able to do this without issue. However, I need to use build 36 of the mouse genome which was last included in ensembl mart 46. I selected this mart and the mouse dataset as follows: mart<-useMart(biomart="ensembl_mart_46",

Dear Peter, I am running your g.test() with the william's correction but I have a question about the input numbers. These are my data: "Our data are consistent with those obtained using microarray comparative genome hybridization in that we found significantly fewer variants per Mb on the X compared to the autosomal chromosomes (152 versus 336 respectively, G = 93.4, P < 2e-16, df =

Hi, List, Sorry in advance if this turns out to be a stupid question -- I've been trying to work it out for awhile, and I don't have any new ideas -- I'm very new to R documentation/ LATEX. I am running "R CMD check " on a package that I am trying to write; the only warning is: * checking for missing documentation entries ... WARNING Undocumented data sets: Einter KG All

Hello, Anyone on this group using / implementing * and hardware certified for use in Europe ? I believe that ISDN4Linux cards mostly have telecomm certificates, so using them should be safe on the client side. Are there any major issues / problems associated with using such cards with * ? I am talking about a small / very small office with single - few lines. All the best, Piotr Adamiak --

Hi, Recently added to doc/NEWS.Rd: 'R CMD check' now gives a warning rather than a note if it finds inefficiently compressed datasets. With 'bzip2' and 'xz' compression having been available since R 2.10.0, there is no excuse for not using them. Why isn't a note enough for this? Generally speaking, warnings are for things that are dangerous, or unsafe,

Hello,I am a little bit struggling with the following: I would like to draw a coplot and in each panel draw the curve and display the coefficients of the regression model y~a*x^b. I thought of running nls(y~a*x^b,...) in panel=function(x,y...){} when calling coplot. How can I do this? Alternatively, I could do the regression before graphing with coplot and just use the panel function to draw the

Hi, I have a set of genes and its chromosomal physical position in a text file. I want to view those genes in the chromosome using R package GenePlotter. Could any one please tell how to view this. Thanks in advance. Yours sincerely, S.Mahalakshmi [[alternative HTML version deleted]]

Dear R-help We have a regression problem which could be solved elegantly if we could figure out how to get the R residuals() function to accept missing dependent variables. We have ~20000 gene-expression vectors y, each being measured on the same set of individuals, but each having a small random number of missing values. For each expression vector we wish to search across the genome

Hi all, We are using two methods to identify SNPs. One is based on resequencing the genome and aligning the reads to the sequenced genome to identify SNPs (data available for 44 individuals). Another is based on SNP array with selected loci (30000 loci, 870 individuals). I want to compare the results from the resequencing based minor allele frequency and Array based minor allele frequency.

Hi, I am given the following table: > head(hsa_refseq) chr genome region start stop nu strand nu.1 nu.2 gene_id 1 chr1 hg19_refGene CDS 67000042 67000051 0 + 0 gene_id NM_032291 2 chr1 hg19_refGene exon 66999825 67000051 0 + . gene_id NM_032291 3 chr1 hg19_refGene CDS 67091530 67091593 0 + 2 gene_id NM_032291 4 chr1 hg19_refGene exon

Comments interspersed, and some code at the end. On Mon, 5 Mar 2018, Sariya, Sanjeev wrote: > Thanks. I think nabble is good for programming questions. Bear with me > if I'm incorrect. You may have found R-help archives at Nabble, but R-help has nothing to do with Nabble. > > Data: Genomics SNP information I know almost nothing about using R for genomics. > Goal: I need

Dear R community, For 100 sites at human chromosomes, I ran two tests, one is to consider an experiment measurement as a continuous variable, so doing multiple regression; the other is to compare top 25% samples to bottom 25% samples based on values of the measured variable, so categorical analysis. A total of 16 sites show significance; In the following results, I only show five variables (

I've just started learning R, so I'm still on the steep part of the learning curve, but my enthusiasm was heightened by learning that there's a very nice implementation of mosaicplot(). As a learning project, I've already done a basic implementation of a pairs.table() function which does a mosaic scatterplot matrix, and now I'm trying to do conditional mosaic plots (discrete

Hi all, SETUP: I have pairwise data on 22 chromosomes. Data matrix X for a given chromosome looks like this: 1 13 58 1.12 6 142 56 1.11 18 307 64 3.13 22 320 58 0.72 Where column 1 is person ID 1, column 2 is person ID 2, column 3 can be ignored, and column 4 is how much chromosomal sharing those two individuals have in some small portion of the chromosome. There are 9000 individual people, and

Hello, I have an R script that I use as a template to perform a task for multiple files (in this case, multiple chromosomes). What I would like to do is to utilize a simple loop to parse through each chromosome number so that I don't have to type the same code over and over again in the R console. I've tried using: for(i in 1:22){ etc.. } and replacing each chromosome number with

Thanks. I think nabble is good for programming questions. Bear with me if I'm incorrect. Data: Genomics SNP information Goal: I need to add Chromosome and SNP position to the data frame I'm using through apply. I'd like to add new column from text processed through apply function. For example: 10:60523:T:G (Column 2) CHR: 10 Position: 60523 Dataset: chr rs ps n_miss allele1