1. Ultra-large alignments using Ensembles of HMMs Nam-phuong Nguyen Institute for Genomic Biology University of Illinois at Urbana-Champaign

2. UPP: Ultra-large alignment UPP: Ultra-large alignments using Phylogeny- aware Profiles Objective: Estimate accurate alignments on large datasets, which may be evolutionarily divergent and contain fragmentary sequences Nguyen N., Mirarab S., Kumar K., and Warnow, T. RECOMB 2015.

3. UPP Algorithmic Strategy

4. RNASim: alignment error Note: All methods given 24 hrs on a 12-core machine. Mafft fails to complete on 200K sequences. Clustal-Omega only completes on 10K dataset. 1 Million RNASim: UPP(Fast) generated an alignment in 12 days compared to 15 days for PASTA. UPP(Fast) resulted in a better alignment (5.7% lower error), but PASTA resulted in a better tree (1.5% lower error).

5. Running Time Wall-clock time used (in hours) given 12 processors

6. Ensemble of HMMs Use a collection of HMMs instead of a single HMM to represent a backbone alignment Improves alignment accuracy, which can lead to better downstream analyses – Phylogenetic placement (SEPP; PSB 2012) – Taxonomic identification (TIPP, Bioinformatics 2014)