Pytrf: a python package for finding tandem repeats from genomic sequences
Background Tandem repeats (TRs) are major sources of genetic variation and important genetic markers. Their expansions are not only involved in gene expression regulation but also associated with many nervous system diseases and cancers. However, there is a lack of an efficient tandem repeat identif...
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| Published in | BMC bioinformatics Vol. 26; no. 1; pp. 151 - 8 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
04.06.2025
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1471-2105 1471-2105 |
| DOI | 10.1186/s12859-025-06168-3 |
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| Summary: | Background
Tandem repeats (TRs) are major sources of genetic variation and important genetic markers. Their expansions are not only involved in gene expression regulation but also associated with many nervous system diseases and cancers. However, there is a lack of an efficient tandem repeat identification tool for seamless integration with larger bioinformatics programs developed with the popular Python language.
Results
We introduce pytrf, a Python package for identification of both exact and approximate TRs from genomic sequences. It allows seamless embedding into other programs developed by Python or using in Python interactive environment and Jupyter notebooks. It also provides command line tools for assisting users to find tandem repeats from FASTA/Q files. Compared to other tools, the pytrf shows the highest performance in aspect of running time with comparable peak memory usage.
Conclusions
Pytrf provides simple interfaces and command line tools to facilitate identification of tandem repeats from genomic sequences. Pytrf can easily be installed from PyPI (
https://pypi.org/project/pytrf
) and the source code is freely available at
https://github.com/lmdu/pytrf
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1471-2105 1471-2105 |
| DOI: | 10.1186/s12859-025-06168-3 |