Print summary information about beam.stats object
Usage
# S3 method for class 'beam.stats'
print(x, ...)Examples
data(beam_stats)
print(beam_stats)
#> Contains 6 association estimate matrices with 10 bootstraps:
#> Association Estimate Matrix of Lesion with MRD29 has dimensions 20 x 11.
#> Association Estimate Matrix of RNA with MRD29 has dimensions 20 x 11.
#> Association Estimate Matrix of Lesion with EFS has dimensions 20 x 11.
#> Association Estimate Matrix of RNA with EFS has dimensions 20 x 11.
#> Association Estimate Matrix of Lesion with OS has dimensions 20 x 11.
#> Association Estimate Matrix of RNA with OS has dimensions 20 x 11.
#>
#> Example Association Estimate Matrix for Lesion with MRD29:
#> boot_0 boot_1 boot_2 boot_3
#> ENSG00000264545_loss -0.19093600 -0.18285072 -0.21417250 -0.20583809
#> ENSG00000147889_loss -0.19931154 -0.17555327 -0.20297360 -0.19104882
#> ENSG00000224854_loss -0.18613078 -0.17555327 -0.21375800 -0.18794477
#> ENSG00000148400_mutation -0.02983458 -0.03084684 0.05543433 -0.01137685
#> ENSG00000099810_loss -0.13672414 -0.12616440 -0.16711568 -0.11536782
#> boot_4
#> ENSG00000264545_loss -0.156257583
#> ENSG00000147889_loss -0.210577002
#> ENSG00000224854_loss -0.163050513
#> ENSG00000148400_mutation -0.001250098
#> ENSG00000099810_loss -0.090666306
#>
#> Example Association Estimate Matrix for RNA with MRD29:
#> boot_0 boot_1 boot_2 boot_3 boot_4
#> ENSG00000121410 0.045547007 0.004894953 0.11539090 0.091368164 0.12737124
#> ENSG00000148584 -0.043899068 -0.027183517 -0.03688248 -0.066976684 -0.06705541
#> ENSG00000175899 0.071592760 0.035710522 0.08890343 0.060304200 0.04032931
#> ENSG00000166535 0.000296431 -0.011542505 -0.07000542 0.003024411 0.03280950
#> ENSG00000184389 0.088934788 0.053931057 0.12269236 0.205216952 0.11770464
#>
#> Example Association Estimate Matrix for Lesion with EFS:
#> boot_0 boot_1 boot_2 boot_3
#> ENSG00000264545_loss 0.311047946 0.192434740 -0.027644863 0.45783281
#> ENSG00000147889_loss 0.355335350 0.212469747 -0.005443877 0.49058097
#> ENSG00000224854_loss 0.358707580 0.212469747 0.010605097 0.52911969
#> ENSG00000148400_mutation -0.008535379 0.101993852 -0.185038910 -0.09593391
#> ENSG00000099810_loss -0.015810223 0.006761143 -0.488404478 -0.18680785
#> boot_4
#> ENSG00000264545_loss 0.6079674
#> ENSG00000147889_loss 0.6584991
#> ENSG00000224854_loss 0.6237131
#> ENSG00000148400_mutation 0.1068464
#> ENSG00000099810_loss 0.2182788
#>
#> Example Association Estimate Matrix for RNA with EFS:
#> boot_0 boot_1 boot_2 boot_3 boot_4
#> ENSG00000121410 0.05921417 0.1825319 0.34583467 0.1120400 0.07337122
#> ENSG00000148584 0.17012792 0.2792833 0.35866190 0.2208551 -0.50231550
#> ENSG00000175899 -0.11536335 -0.1158022 -0.02586119 -5.6659243 -3.05803752
#> ENSG00000166535 0.24454397 0.3871298 0.45451663 0.2155649 0.19137130
#> ENSG00000184389 -0.13690629 -0.2247154 -0.12818200 -0.2024793 -0.02224107
#>
#> Example Association Estimate Matrix for Lesion with OS:
#> boot_0 boot_1 boot_2 boot_3
#> ENSG00000264545_loss 0.8932939 0.82087274 0.7774685 1.007661292
#> ENSG00000147889_loss 0.9489993 0.84854596 0.8068623 1.045121725
#> ENSG00000224854_loss 0.9563505 0.84854596 0.8400789 1.095728463
#> ENSG00000148400_mutation -0.0989406 0.04244735 0.1444102 -0.081025546
#> ENSG00000099810_loss 0.3328451 0.53394399 -0.1096147 0.003899453
#> boot_4
#> ENSG00000264545_loss 1.116271049
#> ENSG00000147889_loss 1.172808630
#> ENSG00000224854_loss 1.139336521
#> ENSG00000148400_mutation 0.008572771
#> ENSG00000099810_loss 0.583670072
#>
#> Example Association Estimate Matrix for RNA with OS:
#> boot_0 boot_1 boot_2 boot_3 boot_4
#> ENSG00000121410 -0.06064136 0.08833406 0.19740235 -0.23032144 0.042520410
#> ENSG00000148584 0.05061313 0.19634699 0.13935280 -0.04349620 -0.308207853
#> ENSG00000175899 0.02594285 0.03512339 0.06672908 -0.11478157 -0.057850041
#> ENSG00000166535 -0.09119894 -0.16775731 -0.97860178 -0.05163522 0.036242601
#> ENSG00000184389 -0.13155891 -0.34544421 -0.27764175 -0.10397644 0.009883494
#>
#> Example Endpoint Data:
#> MRD29 EFS OS
#> PARASZ 0.00 3087+ 3087+
#> PARAYM 0.00 3399+ 3399+
#> PARCVM 0.00 2424+ 2424+
#> PAREGZ 0.49 3087+ 3087+
#> PARFDL 0.00 3075+ 3075+
#>
#> BEAM Model Specifications:
#> name mtx mdl
#> 1 Lesion.MRD29 Lesion lm(MRD29~mtx.row,data=main.data,model=T)
#> 2 RNA.MRD29 RNA lm(MRD29~mtx.row,data=main.data,model=T)
#> 3 Lesion.EFS Lesion coxphf2(EFS~mtx.row,data=main.data,model=T)
#> 4 RNA.EFS RNA coxphf2(EFS~mtx.row,data=main.data,model=T)
#> 5 Lesion.OS Lesion coxphf2(OS~mtx.row,data=main.data,model=T)
#> 6 RNA.OS RNA coxphf2(OS~mtx.row,data=main.data,model=T)
#>
#> BEAM data used to create Association Estimate Matrices:
#> main.data: 265 rows and 8 columns.
#>
#> ID MRD29 RNA.clm Lesion.clm Lesion.id
#> PARASZ PARASZ 0.00 46 21 PARASZ
#> PARAYM PARAYM 0.00 47 108 PARAYM
#> PARCVM PARCVM 0.00 15 84 PARCVM
#> PAREGZ PAREGZ 0.49 170 142 PAREGZ
#> PARFDL PARFDL 0.00 184 175 PARFDL
#>
#> mtx.data:
#> mtx.data Lesion: 265 columns linked to 265 rows of main.data.
#> mtx.data RNA: 264 columns linked to 264 rows of main.data.
#>
#> Lesion:
#> PARWNW PASXUC PATXNR PASYIS PATBGC
#> ENSG00000264545_loss 1 1 1 1 0
#> ENSG00000147889_loss 1 1 1 1 0
#> ENSG00000224854_loss 1 1 1 1 0
#> ENSG00000148400_mutation 1 1 1 1 0
#> ENSG00000099810_loss 1 1 1 1 0
#>
#> RNA:
#> PARFIH PARFPJ PARFXJ PARKLK PARLJA
#> ENSG00000121410 0.4976379 0.29994795 1.13973142 0.32584690 0.35940872
#> ENSG00000148584 0.0000000 0.00000000 0.00000000 0.00000000 0.00000000
#> ENSG00000175899 0.0176369 0.11316706 0.02913480 0.00992041 0.02672925
#> ENSG00000166535 0.0000000 0.02261638 0.01278318 0.01735184 0.00000000
#> ENSG00000184389 0.1067503 1.46126661 0.32734246 0.56042150 0.49385225
#>
#> mtx.anns:
#> Lesion: 20 rows and 2 columns.
#> RNA: 20 rows and 2 columns.
#>
#> Lesion:
#> id gene
#> 1 ENSG00000264545_loss ENSG00000264545
#> 2 ENSG00000147889_loss ENSG00000147889
#> 3 ENSG00000224854_loss ENSG00000224854
#> 4 ENSG00000148400_mutation ENSG00000148400
#> 5 ENSG00000099810_loss ENSG00000099810
#>
#> RNA:
#> id gene
#> 1 ENSG00000121410 ENSG00000121410
#> 2 ENSG00000148584 ENSG00000148584
#> 3 ENSG00000175899 ENSG00000175899
#> 4 ENSG00000166535 ENSG00000166535
#> 5 ENSG00000184389 ENSG00000184389
#>
#> anns.mtch:
#> mtx.data mtx.anns id.clm nrow.mtx nrow.ann nrow.map
#> 1 Lesion Lesion id 20 20 20
#> 2 RNA RNA id 20 20 20
#>
#> set.data: 40 rows assigning sets to data.mtx rows.
#> set.id mtx.id row.id
#> 9 ENSG00000081760 RNA ENSG00000081760
#> 8 ENSG00000094914 RNA ENSG00000094914
#> 25 ENSG00000099810 Lesion ENSG00000099810_loss
#> 19 ENSG00000099810 RNA ENSG00000099810
#> 14 ENSG00000109576 RNA ENSG00000109576
#> 10 ENSG00000114771 RNA ENSG00000114771
#>
#>
#> set.anns: rows of set annotations.
#>
#> boot.index: 11 rows and 265 columns of bootstrap indices.
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1 2 3 4 5
#> [2,] 179 14 195 118 229
#> [3,] 108 8 114 261 29
#> [4,] 55 19 241 218 155
#> [5,] 145 200 211 69 46