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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.