Table 1 Software for predicting structural variations
From: Unraveling genomic variation from next generation sequencing data
| Tool | Single-End | Pair-End | Reference genome | Insertion | Deletion | Inversion | Translocation across chromosomes | Translocation within chromosome | Properties | Input File |
|---|---|---|---|---|---|---|---|---|---|---|
| BreakDancer [61] | X | X | X | X | X | X | • BreakDancerMax for large regions and BreakDancerMini for indels of 10-100 bp | BAM, SAM | ||
| CNV-seq [62] | X | X | X | X | • Shotgun sequencing | Map locations from a BAM file (by SAM tools) | ||||
| • Robust statistical model | ||||||||||
| GASV [63] | X | X | X | X | X | X | • Geometric approach | BAM | ||
| • A SV is pictured as a polygon on a surface | ||||||||||
| • Comparison of SVs across multiple samples | ||||||||||
| HyDRa [64] | X | X | X | X | X | X | • SV breakpoints by clustering discordant paired-end alignments | Tab-delimiteddiscordant paired-end mappings | ||
| MoDIL [65] | X | X | X | • Medium sized (10-50 bp) paired-end indels | Software specific | |||||
| • Able identify shorter heterozygous, as well as homozygous variants with higher accuracy | ||||||||||
| MrFast [66] | X | X | X | • Short sequence reads (>25 bp) | FASTA, FASTQ | |||||
| NovelSeq [67] | X | X | • Long novel sequence insertions | Software specific | ||||||
| • Multiple types of variations | ||||||||||
| PEMer [68] | X | X | X | X | X | X | • PEMer: variations | SVdB API | ||
| • SV-Simulation: simulated paired-end reads | ||||||||||
| • BreakDB: annotations | ||||||||||
| Pindel [69] | X | X | X | X | • Large deletions (1 bp–10 kb) | BAM,SAM,FASTA, FASTQ | ||||
| • Medium sized insertions (1–20 bp) from 36 bp paired-end short reads | ||||||||||
| rSW-seq [70] | X | X | X | X | • Based on an iterative Smith-Waterman dynamic sequence alignment method | Tab-delimited file denoting the tumor/normal status for each of aligned read positions | ||||
| VariationHunter [71] | X | X | X | X | • Evaluation of the entire possible mapping set of positions of each paired-end read and final mapping of the SVs interdependently. | Software specific | ||||
| VarScan [72, 73] | X | X | X | X | • Germline variants (SNPs and indels) in individual samples or pools of samples. | Pileup, VCF | ||||
| • Shared and private variants in multi-sample datasets (with mpileup). | ||||||||||
| • Somatic mutations, LOH events, and germline variants in tumor-normal pairs. | ||||||||||
| • Somatic copy number alterations (CNAs) in tumor-normal exome data. |