Supported by Dr. Osamu Ogasawara and  providing  . |
|
Last data update: 2014.03.03 |
Ranking of cells according to backbone tree structureDescriptionProduces a table of input cells ranked by their position in the backbone tree. Usagecell.ordering.table(b.tree, write.to.tex.file = NULL) Arguments
ValueList of all cells, ranked by position in backbone tree, along with topic information. Examples# Load pre-computed LDA model for skeletal myoblast RNA-Seq data from HSMMSingleCell package: data(HSMM_lda_model) # Recover sampling time (in days) for each cell: library(HSMMSingleCell) data(HSMM_sample_sheet) days.factor = HSMM_sample_sheet$Hours days = as.numeric(levels(days.factor))[days.factor] # Compute near-optimal backbone tree: b.tree = compute.backbone.tree(HSMM_lda_model, days) # Load pre-computed LDA model for skeletal myoblast RNA-Seq data from HSMMSingleCell package: temp.output = tempfile() cell.ordering.table(b.tree, write.to.tex.file = temp.output) Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(cellTree)
Loading required package: topGO
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Loading required package: graph
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: GO.db
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
groupGOTerms: GOBPTerm, GOMFTerm, GOCCTerm environments built.
Attaching package: 'topGO'
The following object is masked from 'package:IRanges':
members
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/cellTree/cell.ordering.table.Rd_%03d_medium.png", width=480, height=480)
> ### Name: cell.ordering.table
> ### Title: Ranking of cells according to backbone tree structure
> ### Aliases: cell.ordering.table
>
> ### ** Examples
>
> # Load pre-computed LDA model for skeletal myoblast RNA-Seq data from HSMMSingleCell package:
> data(HSMM_lda_model)
>
> # Recover sampling time (in days) for each cell:
> library(HSMMSingleCell)
> data(HSMM_sample_sheet)
> days.factor = HSMM_sample_sheet$Hours
> days = as.numeric(levels(days.factor))[days.factor]
>
> # Compute near-optimal backbone tree:
> b.tree = compute.backbone.tree(HSMM_lda_model, days)
Loading required namespace: maptpx
Using start group: 0 (1)
Using rooting method: center.start.group
Using root vertex: 4
Adding branch #1:
[1] 65 53 45 2 55 47 57 48 44 7 19 25 69 66 9 63 18 62 51
[20] 56 16 70 136 133 143 89 78 140 94 100 177 194 141 199 201 181 161 204
[39] 225 236 255 247 246 233 229 259 258 146 235 159 185 191 216 166 149 83 168
[58] 158 8
Using branch width: 0.927 (width.scale.factor: 1.2)
Outliers: 1
Total number of branches: 1 (forks: 0)
Backbone fork merge (width: 0.927): 60 -> 60
Ranking all cells...
> # Load pre-computed LDA model for skeletal myoblast RNA-Seq data from HSMMSingleCell package:
> temp.output = tempfile()
> cell.ordering.table(b.tree, write.to.tex.file = temp.output)
branch node.label cell.name cell.group main.topic topics
[1,] "1" 4 "T0_CT_A06" 0 1 Numeric,5
[2,] "1" 40 "T0_CT_E08" 0 1 Numeric,5
[3,] "1" 13 "T0_CT_B08" 0 1 Numeric,5
[4,] "1" 242 "T72_CT_C11" 72 1 Numeric,5
[5,] "1" 64 "T0_CT_H02" 0 5 Numeric,5
[6,] "1" 15 "T0_CT_C02" 0 1 Numeric,5
[7,] "1" 30 "T0_CT_D08" 0 1 Numeric,5
[8,] "1" 31 "T0_CT_D09" 0 5 Numeric,5
[9,] "1" 49 "T0_CT_F05" 0 5 Numeric,5
[10,] "1" 60 "T0_CT_G08" 0 1 Numeric,5
[11,] "1" 59 "T0_CT_G07" 0 1 Numeric,5
[12,] "1" 10 "T0_CT_B03" 0 1 Numeric,5
[13,] "1" 58 "T0_CT_G04" 0 1 Numeric,5
[14,] "1" 28 "T0_CT_D06" 0 1 Numeric,5
[15,] "1" 234 "T72_CT_B08" 72 5 Numeric,5
[16,] "1" 267 "T72_CT_H08" 72 1 Numeric,5
[17,] "1" 266 "T72_CT_H05" 72 1 Numeric,5
[18,] "1" 196 "T48_CT_E12" 48 1 Numeric,5
[19,] "1" 41 "T0_CT_E09" 0 1 Numeric,5
[20,] "1" 24 "T0_CT_D01" 0 5 Numeric,5
[21,] "1" 150 "T48_CT_A07" 48 1 Numeric,5
[22,] "1" 1 "T0_CT_A01" 0 1 Numeric,5
[23,] "1" 34 "T0_CT_E01" 0 1 Numeric,5
[24,] "1" 65 "T0_CT_H04" 0 1 Numeric,5
[25,] "1" 53 "T0_CT_F11" 0 1 Numeric,5
[26,] "1" 45 "T0_CT_F01" 0 1 Numeric,5
[27,] "1" 26 "T0_CT_D03" 0 1 Numeric,5
[28,] "1" 2 "T0_CT_A03" 0 1 Numeric,5
[29,] "1" 50 "T0_CT_F06" 0 1 Numeric,5
[30,] "1" 20 "T0_CT_C08" 0 1 Numeric,5
[31,] "1" 23 "T0_CT_C12" 0 1 Numeric,5
[32,] "1" 55 "T0_CT_G01" 0 1 Numeric,5
[33,] "1" 5 "T0_CT_A07" 0 1 Numeric,5
[34,] "1" 3 "T0_CT_A05" 0 1 Numeric,5
[35,] "1" 268 "T72_CT_H09" 72 1 Numeric,5
[36,] "1" 47 "T0_CT_F03" 0 1 Numeric,5
[37,] "1" 137 "T24_CT_H01" 24 1 Numeric,5
[38,] "1" 14 "T0_CT_B09" 0 1 Numeric,5
[39,] "1" 39 "T0_CT_E07" 0 1 Numeric,5
[40,] "1" 38 "T0_CT_E06" 0 1 Numeric,5
[41,] "1" 57 "T0_CT_G03" 0 1 Numeric,5
[42,] "1" 43 "T0_CT_E11" 0 1 Numeric,5
[43,] "1" 54 "T0_CT_F12" 0 1 Numeric,5
[44,] "1" 46 "T0_CT_F02" 0 1 Numeric,5
[45,] "1" 33 "T0_CT_D12" 0 1 Numeric,5
[46,] "1" 48 "T0_CT_F04" 0 1 Numeric,5
[47,] "1" 44 "T0_CT_E12" 0 1 Numeric,5
[48,] "1" 86 "T24_CT_B11" 24 1 Numeric,5
[49,] "1" 211 "T48_CT_G10" 48 1 Numeric,5
[50,] "1" 73 "T24_CT_A05" 24 1 Numeric,5
[51,] "1" 7 "T0_CT_A10" 0 1 Numeric,5
[52,] "1" 35 "T0_CT_E03" 0 1 Numeric,5
[53,] "1" 19 "T0_CT_C07" 0 1 Numeric,5
[54,] "1" 25 "T0_CT_D02" 0 1 Numeric,5
[55,] "1" 69 "T0_CT_H12" 0 1 Numeric,5
[56,] "1" 66 "T0_CT_H05" 0 1 Numeric,5
[57,] "1" 27 "T0_CT_D05" 0 2 Numeric,5
[58,] "1" 9 "T0_CT_B01" 0 2 Numeric,5
[59,] "1" 68 "T0_CT_H09" 0 2 Numeric,5
[60,] "1" 182 "T48_CT_D09" 48 2 Numeric,5
[61,] "1" 63 "T0_CT_H01" 0 2 Numeric,5
[62,] "1" 175 "T48_CT_D01" 48 2 Numeric,5
[63,] "1" 112 "T24_CT_E07" 24 2 Numeric,5
[64,] "1" 80 "T24_CT_B03" 24 2 Numeric,5
[65,] "1" 130 "T24_CT_G04" 24 5 Numeric,5
[66,] "1" 96 "T24_CT_C12" 24 5 Numeric,5
[67,] "1" 190 "T48_CT_E05" 48 2 Numeric,5
[68,] "1" 207 "T48_CT_G03" 48 5 Numeric,5
[69,] "1" 107 "T24_CT_D11" 24 5 Numeric,5
[70,] "1" 91 "T24_CT_C07" 24 2 Numeric,5
[71,] "1" 139 "T24_CT_H03" 24 5 Numeric,5
[72,] "1" 167 "T48_CT_C03" 48 2 Numeric,5
[73,] "1" 82 "T24_CT_B06" 24 5 Numeric,5
[74,] "1" 145 "T48_CT_A02" 48 5 Numeric,5
[75,] "1" 214 "T48_CT_H01" 48 5 Numeric,5
[76,] "1" 115 "T24_CT_E12" 24 2 Numeric,5
[77,] "1" 127 "T24_CT_G01" 24 5 Numeric,5
[78,] "1" 22 "T0_CT_C11" 0 5 Numeric,5
[79,] "1" 81 "T24_CT_B05" 24 5 Numeric,5
[80,] "1" 217 "T48_CT_H05" 48 5 Numeric,5
[81,] "1" 106 "T24_CT_D10" 24 5 Numeric,5
[82,] "1" 84 "T24_CT_B08" 24 5 Numeric,5
[83,] "1" 93 "T24_CT_C09" 24 5 Numeric,5
[84,] "1" 104 "T24_CT_D08" 24 5 Numeric,5
[85,] "1" 153 "T48_CT_A10" 48 5 Numeric,5
[86,] "1" 88 "T24_CT_C02" 24 5 Numeric,5
[87,] "1" 156 "T48_CT_B01" 48 5 Numeric,5
[88,] "1" 74 "T24_CT_A07" 24 5 Numeric,5
[89,] "1" 213 "T48_CT_G12" 48 5 Numeric,5
[90,] "1" 134 "T24_CT_G10" 24 5 Numeric,5
[91,] "1" 131 "T24_CT_G05" 24 5 Numeric,5
[92,] "1" 218 "T48_CT_H06" 48 5 Numeric,5
[93,] "1" 90 "T24_CT_C05" 24 5 Numeric,5
[94,] "1" 197 "T48_CT_F01" 48 5 Numeric,5
[95,] "1" 116 "T24_CT_F01" 24 2 Numeric,5
[96,] "1" 157 "T48_CT_B02" 48 2 Numeric,5
[97,] "1" 97 "T24_CT_D01" 24 2 Numeric,5
[98,] "1" 18 "T0_CT_C06" 0 2 Numeric,5
[99,] "1" 98 "T24_CT_D02" 24 5 Numeric,5
[100,] "1" 52 "T0_CT_F09" 0 5 Numeric,5
[101,] "1" 117 "T24_CT_F02" 24 5 Numeric,5
[102,] "1" 262 "T72_CT_G10" 72 5 Numeric,5
[103,] "1" 163 "T48_CT_B11" 48 5 Numeric,5
[104,] "1" 92 "T24_CT_C08" 24 5 Numeric,5
[105,] "1" 206 "T48_CT_G02" 48 5 Numeric,5
[106,] "1" 208 "T48_CT_G07" 48 5 Numeric,5
[107,] "1" 151 "T48_CT_A08" 48 5 Numeric,5
[108,] "1" 220 "T48_CT_H08" 48 5 Numeric,5
[109,] "1" 160 "T48_CT_B06" 48 5 Numeric,5
[110,] "1" 71 "T24_CT_A03" 24 5 Numeric,5
[111,] "1" 174 "T48_CT_C11" 48 5 Numeric,5
[112,] "1" 165 "T48_CT_C01" 48 5 Numeric,5
[113,] "1" 180 "T48_CT_D07" 48 5 Numeric,5
[114,] "1" 202 "T48_CT_F09" 48 5 Numeric,5
[115,] "1" 147 "T48_CT_A04" 48 5 Numeric,5
[116,] "1" 193 "T48_CT_E08" 48 5 Numeric,5
[117,] "1" 110 "T24_CT_E04" 24 5 Numeric,5
[118,] "1" 154 "T48_CT_A11" 48 5 Numeric,5
[119,] "1" 162 "T48_CT_B10" 48 5 Numeric,5
[120,] "1" 200 "T48_CT_F05" 48 5 Numeric,5
[121,] "1" 169 "T48_CT_C05" 48 5 Numeric,5
[122,] "1" 170 "T48_CT_C06" 48 2 Numeric,5
[123,] "1" 209 "T48_CT_G08" 48 2 Numeric,5
[124,] "1" 186 "T48_CT_E01" 48 4 Numeric,5
[125,] "1" 210 "T48_CT_G09" 48 2 Numeric,5
[126,] "1" 148 "T48_CT_A05" 48 5 Numeric,5
[127,] "1" 188 "T48_CT_E03" 48 2 Numeric,5
[128,] "1" 124 "T24_CT_F10" 24 2 Numeric,5
[129,] "1" 126 "T24_CT_F12" 24 1 Numeric,5
[130,] "1" 62 "T0_CT_G11" 0 1 Numeric,5
[131,] "1" 21 "T0_CT_C09" 0 5 Numeric,5
[132,] "1" 178 "T48_CT_D04" 48 5 Numeric,5
[133,] "1" 252 "T72_CT_E07" 72 5 Numeric,5
[134,] "1" 184 "T48_CT_D11" 48 5 Numeric,5
[135,] "1" 260 "T72_CT_G06" 72 5 Numeric,5
[136,] "1" 224 "T72_CT_A05" 72 5 Numeric,5
[137,] "1" 240 "T72_CT_C07" 72 5 Numeric,5
[138,] "1" 223 "T72_CT_A01" 72 5 Numeric,5
[139,] "1" 257 "T72_CT_F11" 72 5 Numeric,5
[140,] "1" 179 "T48_CT_D06" 48 5 Numeric,5
[141,] "1" 36 "T0_CT_E04" 0 5 Numeric,5
[142,] "1" 172 "T48_CT_C09" 48 5 Numeric,5
[143,] "1" 264 "T72_CT_H01" 72 5 Numeric,5
[144,] "1" 228 "T72_CT_B01" 72 5 Numeric,5
[145,] "1" 144 "T48_CT_A01" 48 5 Numeric,5
[146,] "1" 245 "T72_CT_D04" 72 5 Numeric,5
[147,] "1" 238 "T72_CT_C04" 72 5 Numeric,5
[148,] "1" 227 "T72_CT_A11" 72 5 Numeric,5
[149,] "1" 17 "T0_CT_C05" 0 5 Numeric,5
[150,] "1" 123 "T24_CT_F09" 24 5 Numeric,5
[151,] "1" 237 "T72_CT_B12" 72 5 Numeric,5
[152,] "1" 222 "T48_CT_H12" 48 5 Numeric,5
[153,] "1" 256 "T72_CT_F10" 72 5 Numeric,5
[154,] "1" 32 "T0_CT_D11" 0 5 Numeric,5
[155,] "1" 243 "T72_CT_D01" 72 5 Numeric,5
[156,] "1" 72 "T24_CT_A04" 24 5 Numeric,5
[157,] "1" 254 "T72_CT_F05" 72 5 Numeric,5
[158,] "1" 105 "T24_CT_D09" 24 5 Numeric,5
[159,] "1" 226 "T72_CT_A09" 72 5 Numeric,5
[160,] "1" 99 "T24_CT_D03" 24 5 Numeric,5
[161,] "1" 251 "T72_CT_E05" 72 5 Numeric,5
[162,] "1" 265 "T72_CT_H03" 72 5 Numeric,5
[163,] "1" 271 "T72_CT_H12" 72 5 Numeric,5
[164,] "1" 253 "T72_CT_F01" 72 5 Numeric,5
[165,] "1" 261 "T72_CT_G08" 72 4 Numeric,5
[166,] "1" 51 "T0_CT_F07" 0 5 Numeric,5
[167,] "1" 67 "T0_CT_H08" 0 1 Numeric,5
[168,] "1" 12 "T0_CT_B07" 0 1 Numeric,5
[169,] "1" 11 "T0_CT_B05" 0 1 Numeric,5
[170,] "1" 29 "T0_CT_D07" 0 1 Numeric,5
[171,] "1" 56 "T0_CT_G02" 0 1 Numeric,5
[172,] "1" 16 "T0_CT_C03" 0 3 Numeric,5
[173,] "1" 70 "T24_CT_A01" 24 3 Numeric,5
[174,] "1" 205 "T48_CT_G01" 48 3 Numeric,5
[175,] "1" 136 "T24_CT_G12" 24 3 Numeric,5
[176,] "1" 113 "T24_CT_E09" 24 3 Numeric,5
[177,] "1" 133 "T24_CT_G08" 24 3 Numeric,5
[178,] "1" 87 "T24_CT_C01" 24 3 Numeric,5
[179,] "1" 142 "T24_CT_H09" 24 3 Numeric,5
[180,] "1" 85 "T24_CT_B09" 24 3 Numeric,5
[181,] "1" 76 "T24_CT_A09" 24 3 Numeric,5
[182,] "1" 143 "T24_CT_H12" 24 3 Numeric,5
[183,] "1" 138 "T24_CT_H02" 24 3 Numeric,5
[184,] "1" 89 "T24_CT_C03" 24 3 Numeric,5
[185,] "1" 101 "T24_CT_D05" 24 3 Numeric,5
[186,] "1" 103 "T24_CT_D07" 24 2 Numeric,5
[187,] "1" 95 "T24_CT_C11" 24 2 Numeric,5
[188,] "1" 78 "T24_CT_B01" 24 3 Numeric,5
[189,] "1" 102 "T24_CT_D06" 24 3 Numeric,5
[190,] "1" 219 "T48_CT_H07" 48 2 Numeric,5
[191,] "1" 140 "T24_CT_H05" 24 3 Numeric,5
[192,] "1" 121 "T24_CT_F07" 24 2 Numeric,5
[193,] "1" 119 "T24_CT_F04" 24 2 Numeric,5
[194,] "1" 37 "T0_CT_E05" 0 2 Numeric,5
[195,] "1" 77 "T24_CT_A10" 24 2 Numeric,5
[196,] "1" 203 "T48_CT_F10" 48 2 Numeric,5
[197,] "1" 212 "T48_CT_G11" 48 2 Numeric,5
[198,] "1" 132 "T24_CT_G06" 24 3 Numeric,5
[199,] "1" 109 "T24_CT_E02" 24 3 Numeric,5
[200,] "1" 122 "T24_CT_F08" 24 3 Numeric,5
[201,] "1" 79 "T24_CT_B02" 24 3 Numeric,5
[202,] "1" 94 "T24_CT_C10" 24 3 Numeric,5
[203,] "1" 100 "T24_CT_D04" 24 3 Numeric,5
[204,] "1" 177 "T48_CT_D03" 48 3 Numeric,5
[205,] "1" 194 "T48_CT_E10" 48 3 Numeric,5
[206,] "1" 141 "T24_CT_H07" 24 3 Numeric,5
[207,] "1" 215 "T48_CT_H02" 48 5 Numeric,5
[208,] "1" 248 "T72_CT_D10" 72 4 Numeric,5
[209,] "1" 199 "T48_CT_F03" 48 3 Numeric,5
[210,] "1" 61 "T0_CT_G09" 0 3 Numeric,5
[211,] "1" 269 "T72_CT_H10" 72 4 Numeric,5
[212,] "1" 198 "T48_CT_F02" 48 2 Numeric,5
[213,] "1" 164 "T48_CT_B12" 48 2 Numeric,5
[214,] "1" 183 "T48_CT_D10" 48 2 Numeric,5
[215,] "1" 189 "T48_CT_E04" 48 2 Numeric,5
[216,] "1" 201 "T48_CT_F07" 48 3 Numeric,5
[217,] "1" 118 "T24_CT_F03" 24 3 Numeric,5
[218,] "1" 120 "T24_CT_F05" 24 3 Numeric,5
[219,] "1" 152 "T48_CT_A09" 48 3 Numeric,5
[220,] "1" 171 "T48_CT_C07" 48 2 Numeric,5
[221,] "1" 125 "T24_CT_F11" 24 2 Numeric,5
[222,] "1" 176 "T48_CT_D02" 48 2 Numeric,5
[223,] "1" 108 "T24_CT_E01" 24 3 Numeric,5
[224,] "1" 155 "T48_CT_A12" 48 2 Numeric,5
[225,] "1" 187 "T48_CT_E02" 48 2 Numeric,5
[226,] "1" 221 "T48_CT_H11" 48 2 Numeric,5
[227,] "1" 181 "T48_CT_D08" 48 3 Numeric,5
[228,] "1" 114 "T24_CT_E11" 24 3 Numeric,5
[229,] "1" 195 "T48_CT_E11" 48 3 Numeric,5
[230,] "1" 161 "T48_CT_B08" 48 3 Numeric,5
[231,] "1" 173 "T48_CT_C10" 48 3 Numeric,5
[232,] "1" 204 "T48_CT_F11" 48 3 Numeric,5
[233,] "1" 225 "T72_CT_A08" 72 3 Numeric,5
[234,] "1" 270 "T72_CT_H11" 72 4 Numeric,5
[235,] "1" 236 "T72_CT_B11" 72 4 Numeric,5
[236,] "1" 250 "T72_CT_E04" 72 4 Numeric,5
[237,] "1" 255 "T72_CT_F07" 72 4 Numeric,5
[238,] "1" 239 "T72_CT_C06" 72 4 Numeric,5
[239,] "1" 230 "T72_CT_B03" 72 4 Numeric,5
[240,] "1" 263 "T72_CT_G11" 72 4 Numeric,5
[241,] "1" 241 "T72_CT_C09" 72 4 Numeric,5
[242,] "1" 244 "T72_CT_D03" 72 3 Numeric,5
[243,] "1" 232 "T72_CT_B05" 72 4 Numeric,5
[244,] "1" 247 "T72_CT_D07" 72 4 Numeric,5
[245,] "1" 246 "T72_CT_D05" 72 4 Numeric,5
[246,] "1" 233 "T72_CT_B06" 72 3 Numeric,5
[247,] "1" 229 "T72_CT_B02" 72 3 Numeric,5
[248,] "1" 249 "T72_CT_D11" 72 3 Numeric,5
[249,] "1" 231 "T72_CT_B04" 72 3 Numeric,5
[250,] "1" 259 "T72_CT_G04" 72 3 Numeric,5
[251,] "1" 192 "T48_CT_E07" 48 3 Numeric,5
[252,] "1" 258 "T72_CT_G03" 72 3 Numeric,5
[253,] "1" 6 "T0_CT_A08" 0 3 Numeric,5
[254,] "1" 75 "T24_CT_A08" 24 3 Numeric,5
[255,] "1" 146 "T48_CT_A03" 48 3 Numeric,5
[256,] "1" 235 "T72_CT_B09" 72 3 Numeric,5
[257,] "1" 159 "T48_CT_B04" 48 3 Numeric,5
[258,] "1" 128 "T24_CT_G02" 24 3 Numeric,5
[259,] "1" 185 "T48_CT_D12" 48 3 Numeric,5
[260,] "1" 191 "T48_CT_E06" 48 3 Numeric,5
[261,] "1" 135 "T24_CT_G11" 24 3 Numeric,5
[262,] "1" 111 "T24_CT_E05" 24 3 Numeric,5
[263,] "1" 216 "T48_CT_H04" 48 3 Numeric,5
[264,] "1" 166 "T48_CT_C02" 48 3 Numeric,5
[265,] "1" 149 "T48_CT_A06" 48 3 Numeric,5
[266,] "1" 129 "T24_CT_G03" 24 3 Numeric,5
[267,] "1" 83 "T24_CT_B07" 24 3 Numeric,5
[268,] "1" 168 "T48_CT_C04" 48 3 Numeric,5
[269,] "1" 158 "T48_CT_B03" 48 3 Numeric,5
[270,] "1" 42 "T0_CT_E10" 0 5 Numeric,5
[271,] "1" 8 "T0_CT_A11" 0 3 Numeric,5
>
>
>
>
>
> dev.off()
null device
1
>
|
Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and