Hi
On 24 Jan 2007 at 18:26, Jenny persson wrote: Date sent: Wed, 24 Jan 2007 18:26:17 +0100 (CET) From: Jenny persson <[EMAIL PROTECTED]> To: r-help@stat.math.ethz.ch Subject: Re: [R] keep track of selected observations over time > > Thanks Peter, I forgot that the mailinglist only accept the pdf and > ps. file. > Well, not sure if I understand what you want (your example is not reproducible), but a boxplot beside of making actual plot also returns invisibly a structure for plotting, actually a list. So you can call b.str<- boxplot(.....) and if you go through b.str you can find $out and $group values, which indicate outliers. Then you can do e.g. sel <- your.data[,2] %in% b.str$out[ddd$group == 1] to get logical vector which points are marked as outliers in your first column.Then your.data[sel,] gives you appropriate rows which you can use e.g. for adding lines lines(1:4, your.data[sel,][1,-1]) HTH Petr > Here is my problem again: > > Attached is a graph of four boxplots from one patient s data at > four time points, i.e. each boxplot presents the data at each time > point. At day 0 there are 5 extreme values from five peptide > sequences (please see the below data). Since the response is > changing over time, some of these five extreme values at day 0 may > be lower or higher at day 56, 112 and 252. How can I trace the > location of each peptide sequence that has extreme value at day 0 on > the box plots at day 56, 112 and 252 by color or number coding. For > example, the most five responding peptides can be ranked from 5 > (highest value) to 1 (lowest), so if I do the graph again I would > see the five extreme values at day 0 as numbers 5-1 and each of > these numbers can be any where on the box plot at day 56, 112 and > 252 or instead of the rank numbers using the peptide sequence that > corresponds to each value. Alternatively, the locations of each > peptide sequence at the four time points could be linked by a line. > I would like to repeat this procedure for time point 56, 112 and 252 > as well. That is, at day 56, I want trace where on the box plot at > day 0, 112 and 252, each of the four peptide sequences that have > highest responses is. Again, these four values/peptides can be > presented by different colors, numbers or their peptide sequences > that distinguish them from the other most responding peptides at day > 0, 112 and 252. Can I do the four procedures at the same time, I > mean, if at each time point I want to keep track of where the most > peptide responses from this time point are, then the total number of > peptides at the four time points could be 20. That is for each box > plot, there will be 20 id numbers corresponding to each peptide at > respectively time point. The graph can be kind of messy. > > I have a simple solution of how to see the most responding peptides > changing over time, by plotting each peptide s responses at the > four time points. But I haven t managed the procedure above. If you > have any suggestion how I can do this in R, I would be very > thankful. > > Many thanks > Jenny > > > > Part of the data: > > > pat1[1:20,] > peptides P1_D0 P1_D56 P1_D112 P1_D252 > 1 AAAKKGSEQTLKS -0.06181601 -0.12610877 -0.057898384 -0.02126862 > 2 AAAAPASEDEDDE -0.10972387 -0.17174722 -0.136468783 -0.16262501 > 3 AAAAVSSAKRSLR 0.64156129 1.02630879 0.079891841 0.29757984 > 4 AAAKKGSEQESVK -0.54943062 -0.34311337 -0.338910367 -0.14526498 > 5 AAANLTKIVAYLG -1.72207627 -1.63326368 -0.459839317 -0.63302448 > 6 AACGRISYNDMFE 0.52513671 0.65123495 1.151866644 1.49481479 > 7 AAEAEKAASESLR -0.69366543 -0.47038765 -0.144156174 -0.16042556 > 8 AAEHAQSCRSSAA -0.13373130 -0.09229543 -0.102485597 -0.09782440 > 9 AAERHARLNDSYRLQ -0.19316423 -0.33164239 -0.033764989 -0.11734969 > 10 AAETISAARALPS -0.49632307 -0.53666696 -0.263024663 -0.18231712 > 11 AAEVQRFNRDVDETI -0.80014439 -0.91002202 -0.257201702 -0.12391146 > 12 AAEWTANVTAEFK -0.41544438 -0.10980658 -0.288133150 -0.32022460 > 13 AAGIQWSEEETED -0.04015673 0.08529726 0.002471231 0.07599156 > 14 AAGPALSPVPPVV -0.26795462 -0.36739148 -0.512049278 -0.25449224 > 15 AAGPPPSEGEEST -1.59272674 -1.69729759 -0.843351943 -0.49271773 > 16 AAKIASRQPDSHI -0.40722382 -0.27236225 -0.224539441 -0.32998813 > 17 AAKIQASFRGHMA 2.41234976 2.84435484 0.160852331 0.80197802 > 18 AALDLGGSSDPYV -1.21202038 -1.25109705 -0.259515922 -0.24351352 > 19 AALEPGPSESLTA -2.00256570 -1.57566020 -0.390584034 -0.23682626 > 20 AALLELWELRRQQYE 1.42797600 1.33539104 1.486154861 1.67471189 > > > par(las=1) # all axis labels horizontal > boxplot(data.frame(pat1[,c(2:5)]), pars = list(boxwex = 0.4, > staplewex = 0.8, outwex = .5), > boxfill="lightblue",border=c(3:6), names=c("Day 0", > "56 days","112 days", "252 days"), > col.main="blue", > main ="Averaged peptide response at 4 different > time points for patient 200001",cex.main=0.9, > font.main=0.9) > > > > > > Peter Konings <[EMAIL PROTECTED]> skrev: > Dear Jenny, > > Your post did not have an attachment. The mailing list software strips > most attachments away: see the 'technical details of posting' section > of the posting guide at: http://www.r-project.org/posting-guide.html. > > HTH > Peter. > > On 1/24/07, Jenny persson < [EMAIL PROTECTED] > wrote: Dear > all, > > Attached is a description of my data, graph and the problem which I > need help with. Hope you have time to open the file and help me out. > > Many thanks, > Jenny > > > --------------------------------- > > > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html and provide commented, > minimal, self-contained, reproducible code. > > > > > > > > --------------------------------- > > Petr Pikal [EMAIL PROTECTED] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.