computes the phylogenetically based transcriptome evolutionary index (TEI) shuffling the strata for permutation statistic
Examples
## load example PhyloExpressionSetExample
data("PhyloExpressionSetExample", package="myTAI")
## convert into sparseMatrix - rownames GeneID
spmat <- as(data.matrix(PhyloExpressionSetExample[,-c(1,2)]),
"sparseMatrix")
rownames(spmat) <- PhyloExpressionSetExample$GeneID
## create named Phylostratum vector
ps <- setNames(PhyloExpressionSetExample$Phylostratum,
PhyloExpressionSetExample$GeneID)
## get permutations
rcpp_boottei_parallel(spmat, ps, 100, 1)
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 3.566916 3.556817 3.547190 3.541100 3.524336 3.546987 3.610315
#> [2,] 3.534198 3.547641 3.500310 3.497786 3.496934 3.524459 3.470361
#> [3,] 3.357606 3.375342 3.397485 3.397878 3.392662 3.404672 3.465469
#> [4,] 3.472627 3.481911 3.455790 3.445719 3.461058 3.466215 3.546111
#> [5,] 3.509851 3.521309 3.472822 3.459511 3.453000 3.427345 3.417207
#> [6,] 3.479207 3.480612 3.548691 3.576893 3.593751 3.608122 3.607803
#> [7,] 3.491459 3.500608 3.489502 3.504908 3.525244 3.487995 3.483384
#> [8,] 3.487009 3.470899 3.435151 3.442966 3.442171 3.428429 3.538930
#> [9,] 3.408949 3.419296 3.477547 3.490356 3.513563 3.492094 3.473448
#> [10,] 3.507845 3.487450 3.458533 3.464423 3.445926 3.416150 3.536615
#> [11,] 3.551177 3.542816 3.502160 3.501634 3.494307 3.497645 3.521766
#> [12,] 3.459512 3.456414 3.493547 3.467291 3.437093 3.414908 3.461731
#> [13,] 3.589417 3.590023 3.526621 3.541767 3.553870 3.582897 3.651540
#> [14,] 3.479397 3.479622 3.495841 3.509548 3.519257 3.520539 3.588056
#> [15,] 3.466339 3.456463 3.519237 3.507040 3.496849 3.470835 3.486135
#> [16,] 3.548661 3.548374 3.602497 3.591965 3.611597 3.636848 3.538130
#> [17,] 3.545461 3.537451 3.527095 3.527713 3.520109 3.500605 3.529115
#> [18,] 3.472242 3.466698 3.489779 3.481835 3.499482 3.505475 3.456552
#> [19,] 3.593918 3.591593 3.548466 3.542964 3.522099 3.531684 3.582189
#> [20,] 3.513506 3.509633 3.506214 3.507759 3.476685 3.481765 3.501510
#> [21,] 3.500870 3.487301 3.488295 3.503671 3.501286 3.543199 3.525020
#> [22,] 3.488464 3.502631 3.520486 3.518701 3.522567 3.522942 3.533909
#> [23,] 3.553382 3.548433 3.539634 3.536889 3.533614 3.549921 3.488211
#> [24,] 3.407674 3.425733 3.463368 3.441594 3.454209 3.450710 3.538913
#> [25,] 3.464242 3.465876 3.458397 3.472812 3.493048 3.513758 3.532910
#> [26,] 3.486832 3.500343 3.537708 3.534003 3.542846 3.543240 3.529718
#> [27,] 3.461931 3.436660 3.464425 3.470268 3.482177 3.546141 3.518292
#> [28,] 3.507834 3.509553 3.484045 3.495678 3.492173 3.472465 3.499535
#> [29,] 3.409692 3.414850 3.480056 3.467813 3.462241 3.492830 3.480792
#> [30,] 3.549194 3.574680 3.566155 3.558213 3.540080 3.538330 3.492092
#> [31,] 3.457202 3.472915 3.485026 3.474085 3.493329 3.534298 3.577096
#> [32,] 3.530444 3.568592 3.560767 3.541830 3.542574 3.529348 3.535941
#> [33,] 3.524846 3.525334 3.505708 3.510288 3.511532 3.489678 3.530420
#> [34,] 3.514538 3.505311 3.511990 3.503023 3.450676 3.472473 3.579248
#> [35,] 3.546102 3.568071 3.562425 3.563931 3.572814 3.559912 3.438919
#> [36,] 3.603013 3.625994 3.624465 3.623986 3.603119 3.575133 3.518908
#> [37,] 3.535783 3.534328 3.527629 3.524516 3.538751 3.584382 3.538032
#> [38,] 3.452588 3.461741 3.461378 3.459030 3.446573 3.422196 3.443471
#> [39,] 3.541996 3.551547 3.573238 3.564425 3.551889 3.540266 3.574197
#> [40,] 3.468341 3.463104 3.465821 3.482534 3.507857 3.517742 3.583751
#> [41,] 3.559680 3.554451 3.562509 3.560024 3.570545 3.559698 3.524042
#> [42,] 3.437595 3.433448 3.420592 3.410685 3.463410 3.503916 3.521591
#> [43,] 3.510934 3.499237 3.549895 3.545474 3.544501 3.501809 3.489023
#> [44,] 3.477442 3.473121 3.493895 3.481838 3.495500 3.483939 3.448574
#> [45,] 3.536267 3.545657 3.529890 3.508065 3.498059 3.512241 3.481105
#> [46,] 3.493228 3.484405 3.469756 3.502972 3.537494 3.513390 3.503110
#> [47,] 3.469873 3.483253 3.487925 3.484879 3.482034 3.465706 3.415114
#> [48,] 3.405678 3.411215 3.401663 3.407068 3.420510 3.401310 3.457431
#> [49,] 3.474792 3.458558 3.503919 3.510745 3.494545 3.499279 3.488800
#> [50,] 3.542396 3.538833 3.465700 3.492162 3.506525 3.504975 3.530542
#> [51,] 3.535879 3.551598 3.539334 3.538256 3.545303 3.519570 3.477051
#> [52,] 3.550740 3.528969 3.514541 3.524092 3.498563 3.511365 3.594560
#> [53,] 3.512640 3.516243 3.531494 3.543127 3.553069 3.523205 3.469154
#> [54,] 3.441339 3.420170 3.410676 3.414469 3.447546 3.453555 3.408427
#> [55,] 3.471964 3.471891 3.502958 3.491020 3.463266 3.464355 3.535490
#> [56,] 3.427498 3.471607 3.483059 3.457327 3.461350 3.451391 3.412728
#> [57,] 3.390738 3.381094 3.387653 3.387717 3.381072 3.398089 3.431145
#> [58,] 3.471806 3.493667 3.501664 3.506702 3.485902 3.483350 3.562995
#> [59,] 3.513408 3.511099 3.463542 3.460346 3.463325 3.445745 3.446450
#> [60,] 3.548987 3.535387 3.508439 3.513250 3.517553 3.516268 3.454245
#> [61,] 3.459244 3.462512 3.439336 3.439665 3.430908 3.449370 3.537199
#> [62,] 3.528820 3.541863 3.553194 3.566233 3.569500 3.549607 3.482942
#> [63,] 3.512913 3.526940 3.539288 3.547901 3.557025 3.524070 3.488800
#> [64,] 3.429328 3.441455 3.426769 3.426163 3.429860 3.441704 3.408680
#> [65,] 3.514825 3.493430 3.469126 3.472243 3.461237 3.457805 3.477700
#> [66,] 3.535850 3.515099 3.523755 3.526839 3.518608 3.494019 3.561283
#> [67,] 3.543943 3.568615 3.558857 3.545719 3.525720 3.506332 3.455843
#> [68,] 3.457494 3.452715 3.483116 3.479548 3.495375 3.494818 3.512284
#> [69,] 3.556689 3.560911 3.547900 3.550981 3.536084 3.511140 3.514528
#> [70,] 3.576095 3.542792 3.518521 3.529466 3.561886 3.584819 3.569546
#> [71,] 3.460255 3.458154 3.466173 3.464082 3.491268 3.520450 3.465787
#> [72,] 3.489870 3.504583 3.492721 3.483221 3.516134 3.480552 3.526163
#> [73,] 3.565275 3.555781 3.590312 3.582209 3.561950 3.530203 3.477379
#> [74,] 3.456832 3.435365 3.442593 3.436294 3.424102 3.407609 3.470972
#> [75,] 3.518741 3.509378 3.486199 3.492712 3.490922 3.468254 3.532867
#> [76,] 3.547977 3.534506 3.513805 3.519907 3.519024 3.503940 3.467622
#> [77,] 3.489534 3.470411 3.478761 3.477187 3.480596 3.488422 3.401717
#> [78,] 3.449134 3.444879 3.458086 3.479836 3.491031 3.504157 3.399491
#> [79,] 3.394193 3.374749 3.368094 3.389310 3.363745 3.350528 3.456542
#> [80,] 3.564935 3.557254 3.563517 3.567423 3.576792 3.580334 3.573717
#> [81,] 3.552242 3.554586 3.553708 3.542257 3.518898 3.532190 3.476274
#> [82,] 3.517196 3.534652 3.538155 3.528778 3.543475 3.542918 3.490369
#> [83,] 3.567749 3.534294 3.560423 3.549473 3.548812 3.515743 3.549753
#> [84,] 3.505715 3.486341 3.453009 3.472062 3.478901 3.525022 3.527044
#> [85,] 3.579870 3.563866 3.561502 3.564734 3.572695 3.556270 3.558302
#> [86,] 3.516002 3.504380 3.502050 3.501303 3.527174 3.560340 3.479186
#> [87,] 3.526645 3.532238 3.538296 3.538844 3.539269 3.525972 3.553540
#> [88,] 3.567740 3.565264 3.577219 3.580738 3.578154 3.588189 3.522173
#> [89,] 3.604628 3.594812 3.559033 3.561986 3.541055 3.550015 3.576506
#> [90,] 3.473569 3.465694 3.451987 3.446574 3.491626 3.503490 3.447729
#> [91,] 3.465374 3.437130 3.413644 3.428836 3.424495 3.448511 3.471272
#> [92,] 3.433315 3.421044 3.426212 3.437771 3.449330 3.467569 3.472174
#> [93,] 3.573668 3.570048 3.580143 3.555203 3.567199 3.555117 3.543607
#> [94,] 3.552974 3.551379 3.529226 3.540128 3.556554 3.553650 3.566818
#> [95,] 3.501626 3.496214 3.518929 3.512961 3.493982 3.452318 3.476498
#> [96,] 3.589291 3.556398 3.550927 3.519226 3.496181 3.503583 3.608661
#> [97,] 3.552474 3.541169 3.536691 3.524852 3.500267 3.535176 3.517314
#> [98,] 3.516473 3.517547 3.485642 3.481296 3.471147 3.473377 3.495569
#> [99,] 3.488285 3.521839 3.502380 3.503991 3.530350 3.499782 3.504148
#> [100,] 3.577905 3.562508 3.532110 3.533888 3.535360 3.531336 3.472564