TRAL 2.0: Tandem Repeat Detection With Circular Profile Hidden Markov Models and Evolutionary Aligner

Matteo Delucchi; Paulina Näf; Spencer Bliven; Maria Anisimova

doi:10.3389/fbinf.2021.691865

TRAL 2.0: Tandem Repeat Detection With Circular Profile Hidden Markov Models and Evolutionary Aligner

Front Bioinform. 2021 Jun 25:1:691865. doi: 10.3389/fbinf.2021.691865. eCollection 2021.

Authors

Matteo Delucchi^{1

2}, Paulina Näf^{1

2}, Spencer Bliven^{1

2

3}, Maria Anisimova^{1

2}

Affiliations

¹ Institute of Applied Simulations, School of Life Sciences und Facility Management, Zurich University of Applied Sciences, Wädenswil, Switzerland.
² SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
³ Laboratory for Scientific Computing and Modelling, Paul Scherrer Institute, Villigen PSI, Villigen, Switzerland.

Abstract

The Tandem Repeat Annotation Library (TRAL) focuses on analyzing tandem repeat units in genomic sequences. TRAL can integrate and harmonize tandem repeat annotations from a large number of external tools, and provides a statistical model for evaluating and filtering the detected repeats. TRAL version 2.0 includes new features such as a module for identifying repeats from circular profile hidden Markov models, a new repeat alignment method based on the progressive Poisson Indel Process, an improved installation procedure and a docker container. TRAL is an open-source Python 3 library and is available, together with documentation and tutorials via vital-it.ch/software/tral.

Keywords: bioinformatics; computational biology; genome annotation; profile hidden markov models; protein sequence analysis; tandem repeats.