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Table 1 Factors considered and their levels or possible values, together with acronyms used through the text

From: Identifying restrictions in the order of accumulation of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

Factor Description Values
Model Evolutionary model of cancer progression exp, Bozic, McF_4, McF_6
sh Penalization of deviations from monotonicity 0, Inf (for )
True graph The true graph: the structure that encodes the order restrictions. All possible combinations of Number of nodes and Conjunction 11-A, 11-B, 9-A, 9-B, 7-A, 7-B
Number of nodes (NumNodes) Number of genes or alterations 11, 9, 7
Conjunction Whether or not the graph has conjunctions Yes, No
Sample size (S.Size) Number of samples used for reconstructing the graph 100, 200, 1000
Sampling time (S.Time) When the sample is taken Last, unif (for uniform)
Sampling type (S.Type) How tissue is collected singleC (for single cell), wholeT_0.5 (whole tumor, detection threshold=0.5), wholeT_0.01 (whole tumor, detection threshold=0.1)
Filtering Method for selecting drivers, or filtering passengers, when the true drivers are not known S1, S5, J1, J5 (for frequency of Single event and Joint frequency of events, with thresholds 1% and 5% respectively)
Method Method for inferring the order restrictions CBN, CBN-A, DiP, DiP-A, OT, OT-A
  1. The within-data set factors, Filtering and Method (see text), are shown in italics. All other factors are among-data set factors. Sampling scheme, used through the text, refers to when (S.Time) and how (S.Type) we sample.