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trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses
Open accessAbstract
Summary: Multiple sequence alignments are central to many areas of bioinformatics. It has been shown that the removal of poorly aligned regions from an alignment increases the quality of subsequent analyses. Such an alignment trimming phase is complicated in large-scale phylogenetic analyses that deal with thousands of alignments. Here, we present trimAl, a tool for automated alignment trimming, which is especially suited for large-scale phylogenetic analyses. trimAl can consider several parameters, alone or in multiple combinations, for selecting the most reliable positions in the alignment. These include the proportion of sequences with a gap, the level of amino acid similarity and, if several alignments for the same set of sequences are provided, the level of consistency across different alignments. Moreover, trimAl can automatically select the parameters to be used in each specific alignment so that the signal-to-noise ratio is optimized. Availability: trimAl has been written in C++, it is portable to all platforms. trimAl is freely available for download (http://trimal.cgenomics.org) and can be used online through the Phylemon web server (http://phylemon2.bioinfo.cipf.es/). Supplementary Material is available at http://trimal.cgenomics.org/publications. Contact: tgabaldon@crg.es
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Catanach, T. A., Halley, M. R., & Pirro, S. (2025) · Biological Journal of the Linnean Society · doi:10.1093/biolinnean/blae028 · Cited by 76
Phosphonate production by marine microbes: exploring new sources and potential function
Acker, M., Hogle, S. L., Berube, P. M., Hackl, T., Coe, A., Stepanauskas, R., Chisholm, S. W., & Repeta, D. J. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2113386119 · Cited by 76
Marcet-Houben, M., Marceddu, G., & Gabaldón, T. (2009) · BMC Evolutionary Biology · doi:10.1186/1471-2148-9-295 · Cited by 75
Self-citationBiological processes modulating longevity across primates: a phylogenetic genome-phenome analysis
Muntané, G., Farré, X., Rodríguez, J. A., Pegueroles, C., Hughes, D. A., de Magalhães, J. P., Gabaldón, T., & Navarro, A. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy105 · Cited by 73
Self-citationStructure of the DASH/Dam1 complex shows its role at the yeast kinetochore-microtubule interface
Jenni, S., & Harrison, S. C. (2018) · Science · doi:10.1126/science.aar6436 · Cited by 72
A YidC-like protein in the archaeal plasma membrane.
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The little skate genome and the evolutionary emergence of wing-like fins
Marlétaz, F., de la Calle-Mustienes, E., Acemel, R. D., Paliou, C., Naranjo, S., Martínez-García, P. M., Cases, I., Sleight, V. A., Hirschberger, C., Marcet-Houben, M., et al. (2023) · Nature · doi:10.1038/s41586-023-05868-1 · Cited by 71
Self-citationStepwise pathway for early evolutionary assembly of dissimilatory sulfite and sulfate reduction
Neukirchen, S., Pereira, I. A. C., & Sousa, F. L. (2023) · The ISME Journal · doi:10.1038/s41396-023-01477-y · Cited by 70
Evolutionary diversification of methanotrophic ANME-1 archaea and their expansive virome
Laso-Pérez, R., Wu, F., Crémière, A., Speth, D. R., Magyar, J. S., Zhao, K., Krupovic, M., & Orphan, V. J. (2023) · Nature Microbiology · doi:10.1038/s41564-022-01297-4 · Cited by 68
The evolutionary history of genes involved in spoken and written language: beyond FOXP2
Mozzi, A., Forni, D., Clerici, M., Pozzoli, U., Mascheretti, S., Guerini, F. R., Riva, S., Bresolin, N., Cagliani, R., & Sironi, M. (2016) · Scientific Reports · doi:10.1038/srep22157 · Cited by 67
Endosymbiotic gene transfer in tertiary plastid-containing dinoflagellates
Burki, F., Imanian, B., Hehenberger, E., Hirakawa, Y., Maruyama, S., & Keeling, P. J. (2014) · Eukaryotic Cell · doi:10.1128/ec.00299-13 · Cited by 67
“This procedure generated 1,982 and 4,117 fasta files containing at least 5 sequences for dinotoms and Kareniaceae, respectively, which were subjected to a first round of alignment using MAFFT in auto mode (56), poorly aligned site-trimming using TRIMAL (57), and rapid maximum likelihood (ML) tree reconstructions using…”
MethodAdaptive evolution of the enigmatic Takakia now facing climate change in Tibet
Hu, R., Li, X., Hu, Y., Zhang, R., Lv, Q., Zhang, M., Sheng, X., Zhao, F., Chen, Z., Ding, Y., et al. (2023) · Cell · doi:10.1016/j.cell.2023.07.003 · Cited by 55
Transposon-encoded nucleases use guide RNAs to promote their selfish spread
Meers, C., Le, H. C., Pesari, S. R., Hoffmann, F. T., Walker, M. W. G., Gezelle, J., Tang, S., & Sternberg, S. H. (2023) · Nature · doi:10.1038/s41586-023-06597-1 · Cited by 60
The monoaminergic system is a bilaterian innovation
Goulty, M., Botton-Amiot, G., Rosato, E., Sprecher, S. G., & Feuda, R. (2023) · Nature Communications · doi:10.1038/s41467-023-39030-2 · Cited by 60
Evolutionary Histories of Type III Polyketide Synthases in Fungi
Navarro-Muñoz, J. C., & Collemare, J. (2020) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.03018 · Cited by 59
“rev15 (build[2013-12-17]; parameters: -automated1) (Capella-Gutiérrez et al., 2009), and the phylogenetic tree was built with IQ-TREE (parameters: -nt AUTO -m MFP +MERGE -alrt 1000 -bb 1000 -bspec GENESITE) (Nguyen et al.”
Unexpected complexity of the ammonia monooxygenase in archaea
(2023) · doi:10.1038/s41396-023-01367-3 · Cited by 58
Metadata
- Authors
- Capella-Gutiérrez, S., Silla-Martínez, J. M., & Gabaldón, T.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-06-08
- Volume
- 25
- Issue
- 15
- Pages
- 1972-1973
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2115888213
- Cited by
- 12,751
- References
- 0
- FWCI
- 12.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.