WarpSTR: determining tandem repeat lengths using raw nanopore signals

Author:

Sitarčík Jozef123,Vinař Tomáš4ORCID,Brejová Broňa4,Krampl Werner125,Budiš Jaroslav123,Radvánszky Ján126,Lucká Mária37

Affiliation:

1. Comenius University Science Park , Bratislava 841 04, Slovakia

2. Geneton Ltd , Bratislava 841 04, Slovakia

3. Slovak Centre of Scientific and Technical Information , Bratislava 811 04, Slovakia

4. Faculty of Mathematics, Physics, and Informatics, Comenius University , Bratislava 842 48, Slovakia

5. Department of Molecular Biology, Faculty of Natural Sciences, Comenius University , Bratislava 841 04, Slovakia

6. Institute of Clinical and Translational Research, Biomedical Research Center, Slovak Academy of Sciences , Bratislava 845 05, Slovakia

7. KInIT—Kempelen Institute of Intelligent Technologies , Bottova, 7939/2A , Bratislava 811 09, Slovakia

Abstract

Abstract Motivation Short tandem repeats (STRs) are regions of a genome containing many consecutive copies of the same short motif, possibly with small variations. Analysis of STRs has many clinical uses but is limited by technology mainly due to STRs surpassing the used read length. Nanopore sequencing, as one of long-read sequencing technologies, produces very long reads, thus offering more possibilities to study and analyze STRs. Basecalling of nanopore reads is however particularly unreliable in repeating regions, and therefore direct analysis from raw nanopore data is required. Results Here, we present WarpSTR, a novel method for characterizing both simple and complex tandem repeats directly from raw nanopore signals using a finite-state automaton and a search algorithm analogous to dynamic time warping. By applying this approach to determine the lengths of 241 STRs, we demonstrate that our approach decreases the mean absolute error of the STR length estimate compared to basecalling and STRique. Availability and implementation WarpSTR is freely available at https://github.com/fmfi-compbio/warpstr

Funder

European Union’s Horizon 2020 research and innovation programme

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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