Table 1.
Methods for detecting somatic mutations
| Objective | Data | Method | Description |
|---|---|---|---|
| Somatic mutation detection |
SNV |
MuTect
[22] |
Designed to detect low-frequency mutations in both whole-genome and exome data. |
| Strelka
[23] |
Can be applied to both whole-genome and whole-exome data. Uses stringent post-call filtration. |
||
| VarScan 2
[24] |
Demonstrates high sensitivity for detecting SNVs in relatively pure tumor samples from both whole-genome and exome data. |
||
| JointSNVMix
[128] |
A probabilistic model that describes the observed allelic counts in both tumor and normal samples. |
||
| CNA or SV |
BIC-Seq
[129] |
Detects CNAs from whole-genome data. |
|
| APOLLOH
[130] |
Predicts loss of heterozygosity regions from whole-genome sequencing data. |
||
| CoNIFER
[131] |
Detects CNAs from exome data. |
||
| BreakDancer
[132] |
Cluster paired-end alignments to detect SVs. One version to detect large aberrations and another to detect smaller indels. |
||
| VariationHunter-CommonLaw
[133], HYDRA
[70] |
Cluster paired-reads, including reads with multiple possible alignments. Support simultaneous analysis of multiple samples. |
||
| GASV/GASVPro
[134,135], PeSV-Fisher
[136] |
Combine paired-read and read-depth analysis to detect SVs. |
||
| Meerkat
[130] |
Combines paired-end split-read and multiple alignment information to detect structural aberrations. |
||
| Delly
[137], Break-Pointer
[138] |
Combines paired-end and split-read signals to detect structural aberrations. |
||
| Tumor purity estimation |
SNV |
ABSOLUTE
[28] |
Originally designed for SNP array data, but may be adapted for whole-genome sequencing data. Handles subclonal populations as outliers. |
| ASCAT
[29] |
Designed for SNP array data, but may be adapted for whole-genome sequencing data. Only considers a single tumor population. |
||
| CNA |
THetA
[30] |
Able to consider multiple subclonal tumor populations, but only if they differ by large CNAs. Designed for whole-genome sequencing data. |
|
| SomatiCA [31] | Only uses aberrations that are identified as clonal to estimate tumor purity. |
CNA, copy number aberration; SNV, single-nucleotide variant; SV, structural variant.
A representative list of software available for the detection of somatic mutations from high-throughput sequencing data of cancer genomes. Some methods detect more than one type of mutation but are listed only once for clarity.