TY - JOUR
T1 - MiteFinderII
T2 - A novel tool to identify miniature inverted-repeat transposable elements hidden in eukaryotic genomes 06 Biological Sciences 0604 Genetics
AU - Hu, Jialu
AU - Zheng, Yan
AU - Shang, Xuequn
N1 - Publisher Copyright:
© 2018 The Author(s).
PY - 2018/11/20
Y1 - 2018/11/20
N2 - Background: Miniature inverted-repeat transposable element (MITE) is a type of class II non-autonomous transposable element playing a crucial role in the process of evolution in biology. There is an urgent need to develop bioinformatics tools to effectively identify MITEs on a whole genome-wide scale. However, most of currently existing tools suffer from low ability to deal with large eukaryotic genomes. Methods: In this paper, we proposed a novel tool MiteFinderII, which was adapted from our previous algorithm MiteFinder, to efficiently detect MITEs from genomics sequences. It has six major steps: (1) build K-mer Index and search for inverted repeats; (2) filtration of inverted repeats with low complexity; (3) merger of inverted repeats; (4) filtration of candidates with low score; (5) selection of final MITE sequences; (6) selection of representative sequences. Results: To test the performance, MiteFinderII and three other existing algorithms were applied to identify MITEs on the whole genome of oryza sativa. Results suggest that MiteFinderII outperforms existing popular tools in terms of both specificity and recall. Additionally, it is much faster and more memory-efficient than other tools in the detection. Conclusion: MiteFinderII is an accurate and effective tool to detect MITEs hidden in eukaryotic genomes. The source code is freely accessible at the website: https://github.com/screamer/miteFinder.
AB - Background: Miniature inverted-repeat transposable element (MITE) is a type of class II non-autonomous transposable element playing a crucial role in the process of evolution in biology. There is an urgent need to develop bioinformatics tools to effectively identify MITEs on a whole genome-wide scale. However, most of currently existing tools suffer from low ability to deal with large eukaryotic genomes. Methods: In this paper, we proposed a novel tool MiteFinderII, which was adapted from our previous algorithm MiteFinder, to efficiently detect MITEs from genomics sequences. It has six major steps: (1) build K-mer Index and search for inverted repeats; (2) filtration of inverted repeats with low complexity; (3) merger of inverted repeats; (4) filtration of candidates with low score; (5) selection of final MITE sequences; (6) selection of representative sequences. Results: To test the performance, MiteFinderII and three other existing algorithms were applied to identify MITEs on the whole genome of oryza sativa. Results suggest that MiteFinderII outperforms existing popular tools in terms of both specificity and recall. Additionally, it is much faster and more memory-efficient than other tools in the detection. Conclusion: MiteFinderII is an accurate and effective tool to detect MITEs hidden in eukaryotic genomes. The source code is freely accessible at the website: https://github.com/screamer/miteFinder.
KW - Genomic analysis
KW - K-mer index
KW - Target site duplication
KW - Terminal inverted repeat
KW - Transposable element
UR - http://www.scopus.com/inward/record.url?scp=85056729948&partnerID=8YFLogxK
U2 - 10.1186/s12920-018-0418-y
DO - 10.1186/s12920-018-0418-y
M3 - 文章
C2 - 30453969
AN - SCOPUS:85056729948
SN - 1755-8794
VL - 11
JO - BMC Medical Genomics
JF - BMC Medical Genomics
M1 - 101
ER -