"BinMat": an R CRAN package tutorial скачать в хорошем качестве

"BinMat": an R CRAN package tutorial

This tutorial covers the usage of the functions in the BinMat R package, that allows for the processing of binary data obtained from fragment analysis methods (such as ISSRs and AFLPs). This application is also available as a GUI on the R shiny apps server: https://clarkevansteenderen.shinyapps... Alternatively, the line of code below can be run in R to fetch the BinMat code from GitHub: shiny::runGitHub("BinMat", "CJMvS") Comments and suggestions are welcome! Find the code used in the tutorial below: ----------------------------------------------------------------------------------------- library(BinMat) #PART 1 issr_reps = read.csv(file.choose()) issr_reps check for unwanted values check.data(issr_reps) get peak numbers peaks.original(issr_reps) remove samples if desired rem = peak.remove(issr_reps, 5) rem consolidate the replicate pairs cons = consolidate(issr_reps) cons get peak numbers for consolidated matrix peaks.consolidated(cons) get error rates errors(cons) #upgma clustering tree upgma(cons) write the file to PC as a csv write.csv(cons, "/home/clarke/Desktop/consolidated.csv") PART 2: grouping issr_groups = read.csv(file.choose()) issr_groups get the group names designated group.names(issr_groups) #upgma clustering tree upgma(issr_groups, fromFile = T) prepare for nmds plot: scree(issr_groups,3) shepard(issr_groups) clrs = c("red", "blue") shps = c(16, 16) plot nmds nmds(issr_groups, colours = clrs, shapes = shps, labs = T)