perform the OncoScore time series analysis for a list of genes and data times
compute.oncoscore.timeseries(
data,
filter.threshold = 0,
analysis.mode = "Log2",
cutoff.threshold = 21.09,
file = NULL
)input data as result of the function perform.query.timeseries
threshold to filter for a minimum number of citations for the genes
logaritmic scores to be computed, i.e., log10, log2, natural log or log5
threshold to be used to asses the oncogenes
should I save the results to text files?
the performed OncoScores time series analysis
data(query.timepoints)
compute.oncoscore.timeseries(query.timepoints)
#> ### Computing oncoscore for timepoint 2012/03/01
#> ### Processing data
#> ### Computing frequencies scores
#> ### Estimating oncogenes
#> ### Results:
#> ASXL1 -> 77.19348
#> IDH1 -> 74.24489
#> IDH2 -> 64.1649
#> SETBP1 -> 34.9485
#> TET2 -> 74.90108
#> ### Computing oncoscore for timepoint 2013/03/01
#> ### Processing data
#> ### Computing frequencies scores
#> ### Estimating oncogenes
#> ### Results:
#> ASXL1 -> 76.31902
#> IDH1 -> 78.71551
#> IDH2 -> 69.99559
#> SETBP1 -> 46.4559
#> TET2 -> 73.89695
#> ### Computing oncoscore for timepoint 2014/03/01
#> ### Processing data
#> ### Computing frequencies scores
#> ### Estimating oncogenes
#> ### Results:
#> ASXL1 -> 77.39202
#> IDH1 -> 81.07946
#> IDH2 -> 73.46995
#> SETBP1 -> 64.97398
#> TET2 -> 70.44331
#> ### Computing oncoscore for timepoint 2015/03/01
#> ### Processing data
#> ### Computing frequencies scores
#> ### Estimating oncogenes
#> ### Results:
#> ASXL1 -> 77.49295
#> IDH1 -> 82.55032
#> IDH2 -> 75.58179
#> SETBP1 -> 63.80208
#> TET2 -> 69.91466
#> ### Computing oncoscore for timepoint 2016/03/01
#> ### Processing data
#> ### Computing frequencies scores
#> ### Estimating oncogenes
#> ### Results:
#> ASXL1 -> 77.8392
#> IDH1 -> 83.11346
#> IDH2 -> 76.75356
#> SETBP1 -> 65.556
#> TET2 -> 69.81125
#> $`2012/03/01`
#> CitationsGene CitationsGeneInCancer PercCit alpha 1/alpha
#> ASXL1 91 83 91.20879 6.507795 0.1536619
#> IDH1 488 408 83.60656 8.930737 0.1119728
#> IDH2 234 172 73.50427 7.870365 0.1270589
#> SETBP1 10 5 50.00000 3.321928 0.3010300
#> TET2 196 169 86.22449 7.614710 0.1313248
#> PercCit*1/alpha OncoScore Clustering
#> ASXL1 14.015315 77.19348 1
#> IDH1 9.361663 74.24489 1
#> IDH2 9.339373 64.16490 1
#> SETBP1 15.051500 34.94850 1
#> TET2 11.323411 74.90108 1
#>
#> $`2013/03/01`
#> CitationsGene CitationsGeneInCancer PercCit alpha 1/alpha
#> ASXL1 149 132 88.59060 7.219169 0.1385201
#> IDH1 753 662 87.91501 9.556506 0.1046408
#> IDH2 336 267 79.46429 8.392317 0.1191566
#> SETBP1 18 11 61.11111 4.169925 0.2398125
#> TET2 302 254 84.10596 8.238405 0.1213827
#> PercCit*1/alpha OncoScore Clustering
#> ASXL1 12.271580 76.31902 1
#> IDH1 9.199493 78.71551 1
#> IDH2 9.468694 69.99559 1
#> SETBP1 14.655206 46.45590 1
#> TET2 10.209010 73.89695 1
#>
#> $`2014/03/01`
#> CitationsGene CitationsGeneInCancer PercCit alpha 1/alpha
#> ASXL1 208 185 88.94231 7.700440 0.1298627
#> IDH1 1002 903 90.11976 9.968667 0.1003143
#> IDH2 439 364 82.91572 8.778077 0.1139202
#> SETBP1 36 29 80.55556 5.169925 0.1934264
#> TET2 430 342 79.53488 8.748193 0.1143093
#> PercCit*1/alpha OncoScore Clustering
#> ASXL1 11.550289 77.39202 1
#> IDH1 9.040302 81.07946 1
#> IDH2 9.445772 73.46995 1
#> SETBP1 15.581571 64.97398 1
#> TET2 9.091579 70.44331 1
#>
#> $`2015/03/01`
#> CitationsGene CitationsGeneInCancer PercCit alpha 1/alpha
#> ASXL1 283 250 88.33922 8.144658 0.12277986
#> IDH1 1300 1188 91.38462 10.344296 0.09667164
#> IDH2 550 467 84.90909 9.103288 0.10985042
#> SETBP1 64 49 76.56250 6.000000 0.16666667
#> TET2 576 452 78.47222 9.169925 0.10905215
#> PercCit*1/alpha OncoScore Clustering
#> ASXL1 10.846277 77.49295 1
#> IDH1 8.834300 82.55032 1
#> IDH2 9.327299 75.58179 1
#> SETBP1 12.760417 63.80208 1
#> TET2 8.557564 69.91466 1
#>
#> $`2016/03/01`
#> CitationsGene CitationsGeneInCancer PercCit alpha 1/alpha
#> ASXL1 350 309 88.28571 8.451211 0.11832624
#> IDH1 1576 1446 91.75127 10.622052 0.09414377
#> IDH2 648 557 85.95679 9.339850 0.10706810
#> SETBP1 89 69 77.52809 6.475733 0.15442266
#> TET2 715 558 78.04196 9.481799 0.10546521
#> PercCit*1/alpha OncoScore Clustering
#> ASXL1 10.446516 77.83920 1
#> IDH1 8.637810 83.11346 1
#> IDH2 9.203230 76.75356 1
#> SETBP1 11.972094 65.55600 1
#> TET2 8.230712 69.81125 1
#>