search for: chr4

...ot;black" "chr04" "LOC_Os04g01040" 30637 37300 "TE_related" "black" ... I have worked on the following code to do this job using function and loop, but it is not working. If someone help me, I would really appreciate!!! The original data frame is Os.chr4.gene.new. Gene <- Os.chr4.gene.new[, c("if_TE_related")] Genecolor <- function(Gene) { lg <-length(Gene) for(i in 1:lg) { if (Gene == "TE_related") {D1 <- (Gene == "black")} if (Gene == " ") {D1 <- (Gene == "orange")} } Gene.co...

...nformation in R. For example: #################example data############## > data V1 V2 V3 V4 V5 V6 V7 1 chr1 500 500 CHH 0 0.5 + 2 chr1 550 550 CHH 0 0.0 + 3 chr2 700 700 CHH 0 0.0 + 4 chr2 1000 1000 CHH 0 0.0 + 5 chr3 100 100 CHH 0 0.0 + 6 chr4 450 450 CG 0 0.0 + 7 chr5 450 450 CHH 0 0.0 + 8 chr5 50034 50034 CHG 0 0.0 + 9 chr7 50055 50055 CHG 0 0.0 + 10 chr10 50063 50063 CHH 0 0.0 + > dput(data) structure(list(V1 = structure(c(1L, 1L, 3L, 3L, 4L, 5L, 6L, 6L, 7L, 2L), .Label = c("chr1", "chr10&q...

..., 0, 1, 2, 2, 1, 1, 0, 2, 1, 2, 0, 1, 2, 2, 2, 0, 1, 1, 0, 0, 0)), .Names = c("y", "h4", "h11"), class = "data.frame", row.names = c(NA, -28L)) # ------------ # Some plots # ------------ # Option 1 require(Rcmdr) with(res, scatter3d(h4,ypred,h11, xlab='Chr4',zlab='Chr11', ylab='Ratio',fit=c("linear","quadratic")) ) # Option 2 require(scatterplot3d) with(res, scatterplot3d(h4,ypred,h11, xlab='Chr4',zlab='Chr11',ylab='Ratio') ) # ------------- # Session info # ------------- R version 2.8...

...= structure(c(3L, 3L, 3L, 3L, 3L, 3L), .Label = c("chr1", "chr10", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16", "chr17", "chr18", "chr19", "chr2", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8", "chr9", "chrX"), class = "factor"), start = c(5291000L, 10988025L, 11767950L, 11840900L, 12267450L, 12276675L), end = c(5291926L, 10988526L, 11768676L, 11841851L, 12268076L, 12277051L), peak...

I have the following xyplot figure: http://img577.imageshack.us/img577/686/filesizeresults12000000.png The data are organized in a matrix file as follows: Type Elements Chromosome Time bedGz 12000000 chr1 14.240 bedGz 12000000 chr2 7.949 bedGz 12000000 chr3 5.103 bedGz 12000000 chr4 5.290 bedGz 12000000 chr5 5.161 ... The x-axis labels in the Chromosome column are ordered lexicographically in my figure ( chr1 > chr10 > chr11 > ... ) ? this is correct. However, the code I use to draw lines between points in the xyplot connects points in numerical order ( chr1 &gt...

...uck and getting extremely frustrated that I can't figure it out. I'm trying to make a fairly simple figure, but also trying to make it look "better" using ggplot2. I have data.frame that contains chrom length 1 chr1 249250621 2 chr2 243199373 3 chr3 198022430 4 chr4 191154276 5 chr5 180915260 6 chr6 171115067 7 chr7 159138663 8 chrX 155270560 9 chr8 146364022 10 chr9 141213431 11 chr10 135534747 12 chr11 135006516 13 chr12 133851895 14 chr13 115169878 15 chr14 107349540 16 chr15 102531392 17 chr16 90354753 18 chr17 81195210 19 chr18...

Hi, I am using the sim1000G R package to simulate data for case/control study. I can not figure out how to manipulate this code to be able to generate 10% or 50% causal SNPs in R. This is whole code provided as example on GitHub: library(sim1000G) vcf_file = "region-chr4-357-ANK2.vcf.gz" #nvariants = 442, ss=1000 vcf = readVCF( vcf_file, maxNumberOfVariants = 442 ,min_maf = 0.0005,max_maf = 0.01) #lowest MAF dim( vcf$gt1 ) #rows represent number of variants, columns represent number of individuals ## Download and use full chromosome genetic map downloadGene...

Hello, I have an input file: http://r.789695.n4.nabble.com/file/n3700031/testOut.txt testOut.txt where col 1 is chromosome, column2 is start of region, column 3 is end of region, column 4 and 5 is base position, column 6 is total reads, column 7 is methylation data, and column 8 is the strand. I would like a summary output file such as:

Hello, Everyone, how to use "loop" to make the process automatic and fast? When compute each sample, the script type in R almost the same, just the input and output file's name is changed(chr1 change to chr2, chr3,chr4...). The first sample's script like this: >chr1=MEDIPS.readAlignedSeqences(BSgenome="hg19", file="chr1",numrows= ) >chr1=MEDIPS.genomeVector(data=chr1, bin_size=50,extend=250) ... ... >write.table(frameschr1.frame500.step250, file="frames.chr1.meth.txt",...

...m using the sim1000G R package to simulate data for case/control study. > I can not figure out how to manipulate this code to be able to generate 10% > or 50% causal SNPs in R. > > This is whole code provided as example on GitHub: > > library(sim1000G) > vcf_file = "region-chr4-357-ANK2.vcf.gz" #nvariants = 442, ss=1000 > > vcf = readVCF( vcf_file, maxNumberOfVariants = 442 ,min_maf = > 0.0005,max_maf = 0.01) #lowest MAF > dim( vcf$gt1 ) #rows represent number of variants, columns represent > number of individuals > > ## Download and use full ch...

...DDDDDDDDDDDDDDDDDD") # 100bp C free sequence query.plus <- DNAString("DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD") # 60bp C free sequence query.minus <- reverseComplement(query.plus) chrList <- c("chr1", "chr2", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8", "chr9", "chr10", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16", "chr17", "chr18", "chr19", "chr20&...