On Fri, 30 May 2008, Sean Davis wrote: > > On Fri, May 30, 2008 at 6:35 AM, Niels H??gslund <nj at="" birc.au.dk=""> wrote: > > Hi, > > > > I have a lot of data frames looking like this (SNP chromosome position and a > > local state ID): > > > > Position State > > 1 3088998 0 > > 2 4215064 6 > > 3 5034491 6 > > 4 5211912 6 > > 5 5697261 6 > > 6 5809727 0 > > 7 6818872 NA > > 8 6867391 0 > > 9 7346904 1 > > 10 7347824 1 > > 11 7358232 1 > > 12 7833686 1 > > 13 8295795 0 > > 14 10755448 0 > > 15 10919778 NA > > 16 11217061 3 > > 17 12463350 3 > > 18 13678626 0 > > 19 13892992 0 > > 20 13965452 0 > > 21 13969222 0 > > ........ > > > > Now, I want to collapse or summarize consecutive occurences of a state into > > a region with a start+end position, > > i.e. something like this: > > > > Position State > > 2 4215064 6 > > 5 5697261 6 > > 9 73469041 1 > > 12 7833686 1 > > 16 11217061 3 > > 17 12463350 3 > > > > Can anyone help me with this? > > The rle() function is one way to do this. You will need to write a > little wrapper function to do exactly what you want, but rle() should > get you going. > > Sean > Indeed. It seems that the combination of rle and split will do the job -- but split reorders the data, so we have a subroutine split.preserveord in s2reg below. The following dputs the example and the code with the print of the result. There must be a better way. > dput(y) structure(list(Position = c(3088998L, 4215064L, 5034491L, 5211912L, 5697261L, 5809727L, 6867391L, 7346904L, 7347824L, 7358232L, 7833686L, 8295795L, 10755448L, 11217061L, 12463350L, 13678626L, 13892992L, 13965452L, 13969222L), State = c(0L, 6L, 6L, 6L, 6L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 3L, 3L, 0L, 0L, 0L, 0L)), .Names = c("Position", "State"), row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 17L, 18L, 19L, 20L, 21L, 22L), class = "data.frame", na.action = structure(c(7L, 8L, 16L), .Names = c("7", "8", "16"), class = "omit")) > dput(s2reg) function (df) { # assumes df[,1] is position, df[,2] is state # and contiguous rows sharing value of state are to be grouped # first a tweak of split() split.preserveord = function(x, disc) { tmpn <- unique(disc) ansscr <- split(x, disc) ord <- match(tmpn, names(ansscr)) ansscr[ord] } # now get rle of state rr = rle(df[, 2]) # etc. tags = make.unique(as.character(rr$value)) ftags = rep(tags, rr$len) sdf = split.preserveord(df, ftags) ra = sapply(sdf, function(x) range(x[, 1])) rownames(ra) = c("start", "end") cbind(t(ra), state = rr$val) } > s2reg(y) start end state 0 3088998 3088998 0 6 4215064 5697261 6 0.1 5809727 6867391 0 1 7346904 7833686 1 0.2 8295795 10755448 0 3 11217061 12463350 3 0.3 13678626 13969222 0 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -------------- next part -------------- The information transmitted in this electronic communica...{{dropped:18}}