Apply assembly algorithms to variant-heavy regions

[ryan-williams]

(summarizing @arahuja on the subject)

Simple Version When many SNVs are found close together, consider dropping them under the assumption that something may have been wrong with the reads there. @arahuja has a PoC of this.

Complex Version In regions where SNVs/SVs are found, run more advanced assembly algorithms, e.g. Heng Li's fermi, contrail, other de-Bruijn's-based ones.

[arahuja]

Related references:

1. Rimmer, A. et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat. Genet. 1–9 (2014). doi:10.1038/ng.3036
2. Rizk, G., Gouin, A., Chikhi, R. & Lemaitre, C. MindTheGap : integrated detection and assembly of short and long insertions. Bioinformatics 30, 1–7 (2014).
3. Narzisi, G. et al. Scalpel: Accurate detection of de novo and transmitted INDELs within exome-capture data using micro-assembly. bioRxiv (2013). doi:10.1101/001370
4. Mose, L. E., Wilkerson, M. D., Hayes, D. N., Perou, C. M. & Joel, S. ABRA : improved coding indel detection via assembly based re- alignment. 1–3 (2014).