Table 1.
Tool* | Data type | Model type | Algorithm type | Refs |
---|---|---|---|---|
Cross-sectional data | ||||
TO-DAG | Bulk, presence/absence of any aberrations | Probabilistic | Combinatorial optimization | 91 |
ct-cbn | CNVs | Probabilistic (non-standard) | Specialized | 113 |
NAM | CNVs | Probabilistic (non-standard) | Maximum likelihood (EM) | 112 |
N/A | CNVs | Distance-based (various) | Several off-the-shelf | 125 |
N/A | CNVs | Maximum parsimony | Combinatorial optimization | 177 |
RESIC (generalized from genes to pathways) | DNAseq-based SNVs and CNVs, and gene expression | Probabilistic (pathway generalization of RESIC) | Specialized (simulation-based) | 118 |
RESIC | DNAseq-based SNVs and CNVs or gene expression | Probabilistic | Specialized (simulation-based) | 117‡,§ |
N/A | Gain/loss events | Probabilistic (non-standard) | Statistical hypothesis testing and PCA | 109 |
METREX | Gene expression | Distance-based (various) | WLS via Fitch (from Phylip), neighbour joining, and FASTME | 123 |
N/A | Gene expression | Distance-based (WLS minimum evolution) | Fitch (from Phylip) | 124 |
unmix | Gene expression | Distance-based (minimum spanning tree) | Combinatorial optimization (with deconvolution) | 139‡,§ |
Rtreemix | Generalized binary mutation array, cross-sectional | Probabilistic (mixture model) | Maximum likelihood (EM) | 115 |
Mtreemix | Generalized mutation array | Probabilistic (mixture model) | Maximum likelihood (EM) | 111§ |
oncotrees | Large CNVs or cytogenetic breaks | Statistical (non-standard) | Combinatorial optimization | 66§ |
oncotrees | Large CNVs or cytogenetic breaks | Distance-based (non-standard) | Combinatorial optimization | 122 |
DiProg | Large CNVs or cytogenetic breaks | Probabilistic | Combinatorial optimization (ILP) | 120 |
oncomodel | Large CNVs or cytogenetic breaks | Probabilistic | Maximum likelihood | 108 |
N/A | Large CNVs or cytogenetic breaks | Statistical (non-standard) | Custom heuristic optimization | 178 |
BML | Mutational array | Probabilistic | Bayesian sampling (MCMC) | 90 |
CAPRI, TRONCO, and PiCnic | Mutational array | Specialized probabilistic (PiCnic is a general pipeline) | Custom heuristic optimization | 121,179,180 |
Single-patient, bulk data | ||||
PhyloSub | SNVs | Probabilistic | Bayesian sampling (MCMC) and maximum likelihood (EM) | 119§ |
BitPhylogeny | Methylation, WGS | Probabilistic | Bayesian sampling (MCMC) | 86§ |
GRAFT | DNAseq-based SNVs, CNVs, and rearrangements | Specialized | Combinatorial optimization | 134 |
Single-patient, multiple-site, bulk data | ||||
cITUP | DNAseq-based SNV VAFs | Probabilistic (joint deconvolution and phylogenetics) | Combinatorial optimization (quadratic programming) | 144 |
MEDICC | DNAseq- or CGH-based CNVs | Minimum evolution | Combinatorial optimization | 85§ |
TuMult | CNVs (large-scale) | Maximum parsimony | Combinatorial optimization | 129§ |
Clomial | DNAseq-based SNV VAFs | Probabilistic | Maximum likelihood (EM) | 142‡ |
PhyloWGS | DNAseq-based SNV and CNV VAFs | Probabilistic | Bayesian sampling (MCMC) | 135§ |
Canopy | DNAseq-based SNV and CNV VAFs | Probabilistic | Bayesian sampling (MCMC) | 137 |
SPRUCE | DNAseq-based SNV and CNV VAFs | Specialized (joint deconvolution and phylogenetics) | Combinatorial enumeration | 136 |
SubcloneSeeker | Any variant with a VAF | Specialized (joint deconvolution and phylogenetics | Combinatorial enumeration | 138 |
AncesTree | SNVs | Weighted parsimony | Combinatorial optimization (ILP) | 131 |
rec-BTP | SNVs | Specialized (joint deconvolution and phylogenetics) | Combinatorial optimization | 130 |
LICHeE | SNVs | Specialized (joint deconvolution and phylogenetics) | Combinatorial optimization | 132 |
SCHISM | Output of a clone prediction program such as PyClone or SciClone | Probabilistic | Maximum likelihood (genetic algorithm) | 143 |
Single-patient, single-cell data | ||||
N/A | FISH | Probabilistic | Maximum likelihood (EM) | 181 |
N/A | FISH | Probabilistic | Maximum likelihood (EM) | 69 |
N/A | FISH | Weighted maximum parsimony (with constraint satisfaction) | Combinatorial optimization (ILP) | 169 |
FISHtrees | FISH | Maximum parsimony (with several different formulations of the optimization problem) | Combinatorial optimization | 84§,149§,151§,152§ |
N/A | FISH | Maximum parsimony (rectilinear) | Combinatorial optimization | 153 |
N/A | qPCR and FISH | Maximum parsimony | Combinatorial optimization (PAUP) | 182 |
OncoNEM | scSeq-based SNVs | Probabilistic | Maximum likelihood (specialized heuristic) | 154§ |
SCITE | scSeq-based SNVs | Probabilistic | Bayesian sampling (MCMC) | 87 |
muttree | SNVs | Probabilistic | Maximum likelihood (specialized optimization) | 89 |
CGH, comparative genomic hybridization; CNV, copy number variant; DNAseq, bulk DNA sequencing; EM, expectation maximization; FISH, fluorescence in situ hybridization; ILP, integer linear programming; MCMC, Markov chain Monte Carlo; MST, minimum spanning tree; N/A, not applicable; PCA, principal components analysis; qPCR, quantitative PCR; scSeq, single-cell sequencing; SNV, single nucleotide variant; VAF, variant allele frequency; WGS, whole-genome sequencing; WLS, weighted least squares.
Additional related tools, including tools that identify subclones by deconvolution, are listed in Supplementary information S1 (table), which also contains more information, including the URLs, for the tools listed here. For consistency with the text, the order of tools is sorted primarily by study type and secondarily by data type. Supplementary information S1 (table) is provided in Excel and includes an explicit study type column to allow the reader to sort the rows in the same way or in other ways.
These studies have some phylogenetic aspects, but do not produce phylogenies as their primary output.
These studies use some of the more important or innovative software packages.