> clockstar.interactive() [1] "Welcome to ClockstaR2" please drag or type in the path to your gene trees file in NEWICK format: ~/Dropbox/BiolLettersRevision/B3_TreeRef4_Random3_Parts1-28branchlengths_newick.trees [1] "reading trees from file: ~/Dropbox/BiolLettersRevision/B3_TreeRef4_Random3_Parts1-28branchlengths_newick.trees" [1] "I read 28 from your file" [1] "The names of your trees are:" [1] "part1" "part2" "part3" "part4" "part5" "part6" "part7" "part8" "part9" "part10" "part11" [12] "part12" "part13" "part14" "part15" "part16" "part17" "part18" "part19" "part20" "part21" "part22" [23] "part23" "part24" "part25" "mol1" "mol2" "mol3" [1] "Calculating sBSDmin distances between all pairs of trees" [1] "Estimating tree distances" [1] "estimating distances 1 of 27" [1] "estimating distances 2 of 27" [1] "estimating distances 3 of 27" [1] "estimating distances 4 of 27" [1] "estimating distances 5 of 27" [1] "estimating distances 6 of 27" [1] "estimating distances 7 of 27" [1] "estimating distances 8 of 27" [1] "estimating distances 9 of 27" [1] "estimating distances 10 of 27" [1] "estimating distances 11 of 27" [1] "estimating distances 12 of 27" [1] "estimating distances 13 of 27" [1] "estimating distances 14 of 27" [1] "estimating distances 15 of 27" [1] "estimating distances 16 of 27" [1] "estimating distances 17 of 27" [1] "estimating distances 18 of 27" [1] "estimating distances 19 of 27" [1] "estimating distances 20 of 27" [1] "estimating distances 21 of 27" [1] "estimating distances 22 of 27" [1] "estimating distances 23 of 27" [1] "estimating distances 24 of 27" [1] "estimating distances 25 of 27" [1] "estimating distances 26 of 27" [1] "estimating distances 27 of 27" [1] "I finished calculating the sBSDmin distances between trees\n" The settings for clustering with ClockstaR are: PAM clustering algorithm K from 1 to number of data subsets-1 SEmax criterion to select the optimal k 500 bootstrap replicates Are these correct? (y/n) n Please select one of the clustering functions bellow:(1-3) (1) PAM (2) CLARA (3) FANNY (See the user manual for package cluster for more details 3 What should be the maximum k to test (the maximum is the number of data subsets - 1) 13 Please type in the criterion to select the optimal k (This can be firstSEmax, Tibs2001max, globalSEmax, firstmax, or globalmax) globalmax How many boostrap replicates should be run for the Gap statistic? 500 [1] "The settings for clustering are complete. The settings are:\n" [1] "cluster function, maximum k, criterion" [1] "FANNY" "13" "globalmax" Clustering k = 1,2,..., K.max (= 13): .. done Bootstrapping, b = 1,2,..., B (= 500) [one "." per sample]: .................................................. 50 .................................................. 100 .................................................. 150 .................................................. 200 .................................................. 250 .................................................. 300 .................................................. 350 .................................................. 400 .................................................. 450 .................................................. 500 [1] "ClockstaR has finished running" [1] "The best number of partitions for your data set is: 12" Do you wish to save the results in a pdf file?(y/n) y What should be the name and path of the output file? ~/Dropbox/BiolLettersRevision/Random3_clockstar $parts.mat k=1 k=2 k=3 k=4 k=5 k=6 k=7 k=8 k=9 k=10 k=11 k=12BEST k=13 part1 1 1 1 1 1 1 1 1 1 1 1 1 1 part2 1 2 2 2 2 2 2 2 2 2 2 2 2 part3 1 1 1 1 1 1 1 1 1 1 1 1 1 part4 1 1 1 1 1 1 1 1 1 3 3 3 3 part5 1 1 1 1 1 1 1 1 1 3 3 3 3 part6 1 2 2 2 2 2 2 3 3 4 4 4 4 part7 1 2 2 2 2 2 2 2 2 5 5 5 5 part8 1 1 1 1 1 1 1 1 1 6 6 6 6 part9 1 1 1 1 1 1 1 4 4 1 1 1 1 part10 1 2 2 2 2 2 2 2 2 5 5 5 5 part11 1 1 1 1 1 1 1 4 4 7 7 7 7 part12 1 2 2 2 2 2 2 2 2 7 8 8 8 part13 1 2 2 2 2 2 2 2 2 2 8 8 8 part14 1 2 1 1 1 1 1 1 1 7 7 7 7 part15 1 1 1 1 1 1 1 1 1 3 3 3 3 part16 1 2 2 2 2 2 2 2 3 8 9 9 9 part17 1 1 1 1 1 1 1 1 1 3 3 3 3 part18 1 2 2 2 2 2 2 5 5 9 10 10 10 part19 1 2 2 2 2 2 2 2 3 4 4 4 4 part20 1 1 1 1 1 1 1 4 4 1 1 1 1 part21 1 2 2 2 2 2 2 3 6 4 4 4 4 part22 1 2 2 2 2 2 2 2 2 5 5 11 11 part23 1 1 1 1 1 1 1 1 1 6 6 6 6 part24 1 2 2 2 2 2 2 2 2 5 5 5 12 part25 1 2 2 2 2 2 2 2 2 5 5 5 5 mol1 1 1 3 3 3 3 3 6 7 10 11 12 13 mol2 1 1 3 3 3 3 3 6 7 10 11 12 13 mol3 1 1 3 3 3 3 3 6 7 10 11 12 13 $range.bsd [1] 0.02626654 0.51505818 $best.k [1] 12 $clusterdata Clustering Gap statistic ["clusGap"]. B=500 simulated reference sets, k = 1..13 --> Number of clusters (method 'firstSEmax', SE.factor=1): 1 logW E.logW gap SE.sim [1,] 0.217695486 0.48938356 0.271688074 0.05616211 [2,] 0.003806828 0.15435097 0.150544145 0.05611335 [3,] -0.401084705 -0.01275089 0.388333815 0.07486960 [4,] -0.401084705 -0.13092536 0.270159349 0.11006474 [5,] -0.401084705 -0.21810292 0.182981782 0.14403088 [6,] -0.401084705 -0.30308943 0.097995279 0.16654870 [7,] -0.401084705 -0.39601852 0.005066186 0.18648149 [8,] -0.739104543 -0.53986701 0.199237538 0.18002112 [9,] -0.897155764 -0.68829121 0.208864559 0.15184307 [10,] -1.208065268 -0.79352527 0.414539993 0.11521487 [11,] -1.341829514 -0.87009871 0.471730808 0.10359873 [12,] -1.431729075 -0.93579186 0.495937211 0.11312019 [13,] -1.491689022 -1.01927166 0.472417360 0.12159733 attr(,"class") [1] "partitions" >