Table 3 Tools for genotyping VNTRs.
From: Rediscovering tandem repeat variation in schizophrenia: challenges and opportunities
VNTR genotyping tool | Algorithm description | Genotype TRs that exceed the read limit? | Detects TRs not annotated in reference? | Other notes/features |
|---|---|---|---|---|
VNTRSeek [66] | Sample TRs are mapped to the reference TRs based on similarity in the repeat consensus patterns, and the TR array profiles. Pairings are confirmed with three types of alignment: (i) longest common subsequence (LCS) comparison of consensus patterns; (ii) profile alignment of TR arrays; and (iii) edit-distance alignment of flanking sequences | No | No | First software developed for genome-wide detection of VNTRs, Each VNTR can be modeled individually, and complex models can be constructed for VNTRs with complex structure, along with VNTR specific confidence scores |
adVNTR [65] | Requires training of separate Hidden Markov Models (HMM) models for each combination of target VNTR and sequencing technologies | Yes | No | Provides a uniform training framework, but permits tailoring the models for complex VNTRs on a case-by-case basis |
adVNTR-NN [67] | Uses shallow neural networks for fast read recruitment followed by sensitive Hidden Markov Models (HMMs) for genotyping | Yes | No | Novel use of neural networks as a filtering strategy could lead to an order of magnitude reduction in compute time |
