Predict cell death from known cell lines

[May Blake]

Hello I have somewhat of a complex study that are I am trying to analyze.

I have 2 known cell line trx (Death) and wte (Lived) based on treatments that were used on them (0 = no treatment and 1=treatment). In addition, the cells were looked at for cell death via a type of staining (cross or byroll). What I would like to do is predict the fate of some other cell lines (tun, op7, t5h and ju8) by using the information that is already known about trx and wte. My interpretation is that, I can do this using a regression model such as a linear model to see which unknown cell lines closely matches the known cells or maybe use some type of agreement test like kappaetc to see which ones matches will but I need recommendations on other best tests that can help me answer this question.

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* Example generated by -dataex-. For more info, type help dataex
clear
input byte replicate str6 Stain byte treatment int trx byte wte int(tun    op7)    byte    t5h    int    ju8
7 "CROSS"  0  4934 18 3470 198 42 231
7 "CROSS"  0  4172 24 2690 179 41 151
7 "CROSS"  0  3667 24 2750 179 40 151
8 "CROSS"  0  8129 21 2750 184 38 146
8 "CROSS"  0  5079 24 2280 170 34 119
8 "CROSS"  0  4589 35 2020 165 32  85
8 "CROSS"  0  3984 30 2120 163 35  98
8 "CROSS"  0  6486 26 2520 182 38 119
9 "CROSS"  0  3829 22 2580 169 39 140
9 "CROSS"  0  3748 31 2200 165 35  97
9 "CROSS"  0  4389 28 1800 147 33  98
9 "CROSS"  0  3299 29 2110 163 34 231
10 "CROSS"  0  4187 21 2650 179 43 140
10 "CROSS"  0  3895 26 1830 142 34  79
10 "CROSS"  0  5799 25 2240 172 36 107
10 "CROSS"  0  4195 24 2730 180 40 151
10 "CROSS"  0  4453 26 2230 170 34 304
11 "CROSS"  0  4099 22 2930 186 40 121
11 "CROSS"  0  6295 23 2070 174 36  97
11 "CROSS"  0  4749 17 3350 173 40 258
11 "CROSS"  0  4647 28 3260 170 37 156
11 "CROSS"  0  5719 18 2670 175 36 134
11 "CROSS"  0  3798 35 2050 164 36  97
11 "CROSS"  0  4425 34 1800 157 37  86
11 "CROSS"  1  3995 30 1980 154 33  86
12 "CROSS"  0  9735 25 2650 177 34 121
12 "CROSS"  0  7140 23 2160 172 36  97
12 "CROSS"  0  3799 22 2640 168 35 121
13 "CROSS"  1  4424 19 3420 203 43 231
13 "CROSS"  1  3955 19 3430 197 43 250
13 "CROSS"  0 15906 21 4290 204 45 350
13 "CROSS"  1  4082 19 3400 200 42 231
14 "CROSS"  0 11995 17 3170 193 37 163
14 "CROSS"  0  5899 18 2410 174 36 134
14 "CROSS"  1 12990 14 3420 192 38 163
14 "CROSS"  1  4181 19 3370 200 43 231
15 "CROSS"  0  9690 17 2830 189 37 131
15 "CROSS"  1 13466 14 3830 201 41 302
15 "CROSS"  0  4697 25 1930 155 35  89
15 "CROSS"  0  4516 18 3370 198 41 250
15 "CROSS"  0  5397 41 2040 155 35  90
16 "BIROLL" 0  4296 21 2130 161 36 105
16 "BIROLL" 1  4060 18 3330 201 44 225
16 "BIROLL" 0  5222 19 3210 201 45 231
16 "BIROLL" 1  5379 14 4060 221 48 302
16 "BIROLL" 0  6303 14 4130 217 45 302
16 "BIROLL" 0  5104 22 3220 200 41 200
16 "BIROLL" 0  6850 25 1990 156 36  97
16 "BIROLL" 1  4816 20 3250 196 40 196
16 "BIROLL" 1 14500 14 3900 204 43 350
16 "BIROLL" 1  4733 19 3300 198 42 231
16 "BIROLL" 0  5172 19 3310 198 42 231
16 "BIROLL" 0  5189 20 3280 200 42 196
17 "BIROLL" 1  4482 25 2200 165 36 105
17 "BIROLL" 1 10371 16 4030 206 43 350
17 "BIROLL" 1  4504 22 3180 193 31 200
17 "BIROLL" 1  4723 19 3200 199 40 231
17 "BIROLL" 1  5886 16 3600 206 46 318
17 "BIROLL" 1  3291 20 2830 195 43 140
17 "BIROLL" 1 10372 16 3880 207 43 231
17 "BIROLL" 1  4010 18 3600 206 46 318
18 "BIROLL" 0 13594 12 4720 230 48 400
20 "BIROLL" 1  8814 21 4060 220 43 350
20 "BIROLL" 1 11385 14 4330 221 44 425
20 "BIROLL" 1  5705 16 3690 212 43 250
20 "BIROLL" 1  5798 18 3700 214 42 231
20 "BIROLL" 1  4890 18 3690 218 42 231
20 "BIROLL" 1  7827 15 4080 222 43 350
21 "BIROLL" 1  6342 17 3740 220 46 225
21 "BIROLL" 1  5788 18 3670 218 43 231
22 "BIROLL" 1 11497 12 4840 233 51 400
23 "BIROLL" 1  6165 15 3720 212 44 302
end

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encode stain, gen(stain1)
bysort treatment stain1: regress trx ju8

end

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encode stain, gen(stain1)
bysort treatment stain1: kappaetc trx ju8

end

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