newick: Generate Newick format tree string from tree list object

In ccfindR: Cancer Clone Finder

Description

Generate Newick format tree string from tree list object

Usage

newick(tree, parent = "1.1", string = "")

Arguments

tree	Tree list object from build_tree
parent	Parent ID
string	Newick string of parent tree

Value

String of newick tree

Examples

set.seed(1)
x <- simulate_whx(nrow=50,ncol=100,rank=5)
s <- scNMFSet(x$x)
s <- vb_factorize(s,ranks=seq(2,8),nrun=5)
tree <- build_tree(s,rmax=5)
nw <- newick(tree=tree)
nw

Example output

Run 1
Rank = 2: Nsteps =31, log(evidence) =-3.220272, hyper = (0.3125798,2.421532,0.2553286,1.090867), dispersion = 1
Rank = 3: Nsteps =40, log(evidence) =-2.301975, hyper = (0.1956184,1.692225,0.1743059,1.03016), dispersion = 1
Rank = 4: Nsteps =90, log(evidence) =-1.915525, hyper = (0.133439,1.341696,0.1292562,0.9847309), dispersion = 1
Rank = 5: Nsteps =101, log(evidence) =-1.910936, hyper = (0.1036276,0.9849012,0.1268327,1.034932), dispersion = 1
Rank = 6: Nsteps =105, log(evidence) =-1.298224, hyper = (0.1065642,0.9108574,0.09708988,0.9640453), dispersion = 1
Rank = 7: Nsteps =75, log(evidence) =-1.337305, hyper = (0.0883038,0.7927825,0.09726714,0.9526487), dispersion = 1
Rank = 8: Nsteps =187, log(evidence) =-1.319013, hyper = (0.08472345,0.7047214,0.07931773,0.8275366), dispersion = 1
Run 2
Rank = 2: Nsteps =43, log(evidence) =-2.985025, hyper = (0.2881739,2.510032,0.2511396,1.066041), dispersion = 0.5093711
Rank = 3: Nsteps =52, log(evidence) =-2.443278, hyper = (0.1834726,1.663126,0.2023086,1.063268), dispersion = 0.6676385
Rank = 4: Nsteps =51, log(evidence) =-1.82324, hyper = (0.1378883,1.358771,0.1377949,0.9858606), dispersion = 0.7315702
Rank = 5: Nsteps =44, log(evidence) =-1.272718, hyper = (0.1279342,1.102526,0.102211,0.9632341), dispersion = 0.8052895
Rank = 6: Nsteps =71, log(evidence) =-1.290593, hyper = (0.1137154,0.8591203,0.08183998,1.025736), dispersion = 0.8359017
Rank = 7: Nsteps =157, log(evidence) =-1.308199, hyper = (0.09161253,0.760215,0.07688123,0.9508089), dispersion = 0.846314
Rank = 8: Nsteps =127, log(evidence) =-1.348637, hyper = (0.07479673,0.6652848,0.0931084,0.9389081), dispersion = 0.8540192
Run 3
Rank = 2: Nsteps =42, log(evidence) =-2.985772, hyper = (0.294905,2.547975,0.2522155,1.058072), dispersion = 0.5638854
Rank = 3: Nsteps =58, log(evidence) =-2.363379, hyper = (0.192261,1.851054,0.1755101,0.9589808), dispersion = 0.6923504
Rank = 4: Nsteps =54, log(evidence) =-1.766811, hyper = (0.1404713,1.448887,0.123031,0.9150137), dispersion = 0.7837938
Rank = 5: Nsteps =59, log(evidence) =-1.25892, hyper = (0.1129743,1.027335,0.1021369,1.039533), dispersion = 0.8278495
Rank = 6: Nsteps =67, log(evidence) =-1.2778, hyper = (0.1051466,0.9334776,0.08698342,0.918255), dispersion = 0.8411773
Rank = 7: Nsteps =90, log(evidence) =-1.314135, hyper = (0.08338692,0.7330196,0.09298199,0.9727505), dispersion = 0.8620945
Rank = 8: Nsteps =89, log(evidence) =-1.340424, hyper = (0.06542349,0.6762856,0.09491738,0.9386752), dispersion = 0.8776436
Run 4
Rank = 2: Nsteps =39, log(evidence) =-2.985024, hyper = (0.2885209,2.558508,0.253911,1.042096), dispersion = 0.6320283
Rank = 3: Nsteps =49, log(evidence) =-2.71742, hyper = (0.1948697,1.755059,0.1770911,1.009096), dispersion = 0.7486985
Rank = 4: Nsteps =47, log(evidence) =-1.815812, hyper = (0.1398367,1.316441,0.1391811,1.004942), dispersion = 0.7913369
Rank = 5: Nsteps =102, log(evidence) =-1.645365, hyper = (0.1039625,1.107128,0.09529263,0.9356816), dispersion = 0.8360058
Rank = 6: Nsteps =83, log(evidence) =-1.285885, hyper = (0.09426568,0.8839006,0.0968866,0.9795459), dispersion = 0.869117
Rank = 7: Nsteps =206, log(evidence) =-1.279008, hyper = (0.08081835,0.8035273,0.09014077,0.8104198), dispersion = 0.8875469
Rank = 8: Nsteps =130, log(evidence) =-1.300439, hyper = (0.06378508,0.6629304,0.09130791,0.8810435), dispersion = 0.8916077
Run 5
Rank = 2: Nsteps =39, log(evidence) =-3.220411, hyper = (0.3099831,2.656032,0.2550805,1.009785), dispersion = 0.68
Rank = 3: Nsteps =50, log(evidence) =-2.559947, hyper = (0.1693791,1.572724,0.1597977,1.120149), dispersion = 0.7872886
Rank = 4: Nsteps =59, log(evidence) =-1.771486, hyper = (0.1394539,1.289718,0.1234046,1.045998), dispersion = 0.8453978
Rank = 5: Nsteps =55, log(evidence) =-1.248135, hyper = (0.1156881,1.069702,0.09765931,0.9793849), dispersion = 0.875252
Rank = 6: Nsteps =156, log(evidence) =-1.267798, hyper = (0.1041198,0.8776958,0.08466639,0.9334439), dispersion = 0.8932445
Rank = 7: Nsteps =106, log(evidence) =-1.300903, hyper = (0.08248962,0.7908929,0.08963676,0.9036839), dispersion = 0.90404
Rank = 8: Nsteps =183, log(evidence) =-1.305394, hyper = (0.07657741,0.6521651,0.07984908,0.8457556), dispersion = 0.911237
[1] "(((5.2:1,5.3:1)4.2:2,5.1:3)2.1:1,(5.5:2,5.4:2)3.2:2);"

ccfindR documentation built on Nov. 8, 2020, 5:12 p.m.