Abstract
Over the past three decades, computational capabilities have grown at such a rapid rate that they have given rise to many computationally heavy science fields such as phylogenomics. As increasingly more genomes are sequenced in the three domains of life, larger and more species-complete phylogenetic tree reconstructions are leading to a better understanding of the tree of life and the evolutionary histories in deep times. However, these large datasets pose unique challenges from a modeling and computational perspective: accurately describing the evolutionary process of thousands of species is still beyond the capability of current models, while the computational burden limits our ability to test multiple hypotheses. Thus, it is common practice to reduce the size of a dataset by selecting species to represent a clade (taxon sampling). Unfortunately, this process is subjective, and comparisons of large tree of life studies show that choice and number of species used in a dataset can alter the topology obtained. Thus, taxon sampling is, in itself, a process that needs to be fully investigated to determine its effect on phylogenetic stability. Here, we present the theory and practical application of an automated pipeline that can be easily implemented to explore the effect of taxon sampling on phylogenetic reconstructions. The application of this approach was recently discussed in a study of Terrabacteria and shows its power in investigating the accuracy of deep nodes of a phylogeny.
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References
Darwin C (1859) On the origin of species by means of natural selection, or preservation of favoured races in the struggle for life. John Murray, London
Delsuc F, Brinkmann H, Philippe H (2005) Phylogenomics and the reconstruction of the tree of life. Nat Rev Genet 6:361–375. https://doi.org/10.1038/nrg1603
Bailey SF, Blanquart F, Bataillon T, Kassen R (2017) What drives parallel evolution? BioEssays 39:e201600176. https://doi.org/10.1002/bies.201600176
Christin PA, Weinreich DM, Besnard G (2010) Causes and evolutionary significance of genetic convergence. Trends Genet 26:400–405. https://doi.org/10.1016/j.tig.2010.06.005
Jetz W, Thomas GH, Joy JB et al (2012) The global diversity of birds in space and time. Nature 491:444–448. https://doi.org/10.1038/nature11631
Losos J (2013) The Princeton guide to evolution. Princeton University Press
Vahdati R, Wagner A (2016) Parallel or convergent evolution in human population genomic data revealed by genotype networks. BMC Evol Biol 16:1–20. https://doi.org/10.1186/s12862-016-0722-0
Clerissi C, Touchon M, Capela D et al (2018) Parallels between experimental and natural evolution of legume symbionts. Nat Commun 9:2264. https://doi.org/10.1038/s41467-018-04778-5
Zeller KA (1995) Phylogenetic relatedness within the genus Erysiphe estimated with morphological characteristics. Mycologia 87:525–531. https://doi.org/10.2307/3760771
Zamani Z, Shahi-Gharahlar A, Fatahi R, Bouzari N (2012) Genetic relatedness among some wild cherry (Prunus subgenus Cerasus) genotypes native to Iran assayed by morphological traits and random amplified polymorphic DNA analysis. Plant Syst Evol 298:499–509. https://doi.org/10.1007/s00606-011-0561-9
Sleator RD (2011) Phylogenetics. Arch Microbiol 193:235–239. https://doi.org/10.1007/s00203-011-0677-x
Lang JM, Darling AE, Eisen JA (2013) Phylogeny of bacterial and archaeal genomes using conserved genes: supertrees and supermatrices. PLoS One 8:e62510. https://doi.org/10.1371/journal.pone.0062510
Rinke C, Schwientek P, Sczyrba A et al (2013) Insights into the phylogeny and coding potential of microbial dark matter. Nature 499:431–437. https://doi.org/10.1038/nature12352
Hug LA, Baker BJ, Anantharaman K et al (2016) A new view of the tree of life. Nat Microbiol 1:16048. https://doi.org/10.1038/nmicrobiol.2016.48
Simion P, Philippe H, Baurain D et al (2017) A large and consistent phylogenomic dataset supports sponges as the sister group to all other animals. Curr Biol 27:958–967. https://doi.org/10.1016/j.cub.2017.02.031
Linard B, Crampton-Platt A, Moriniere J et al (2018) The contribution of mitochondrial metagenomics to large-scale data mining and phylogenetic analysis of Coleoptera. Mol Phylogenet Evol 128:1–11. https://doi.org/10.1016/j.ympev.2018.07.008
Shen H, Jin D, Shu JP et al (2018) Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns. Gigascience 7:1–11. https://doi.org/10.1093/gigascience/gix116
Estrada-Peña A, Cabezas-Cruz A (2019) Phyloproteomic and functional analyses do not support a split in the genus Borrelia (phylum Spirochaetes). BMC Evol Biol 19:54. https://doi.org/10.1186/s12862-019-1379-2
Ashkenazy H, Kliger Y (2010) Reducing phylogenetic bias in correlated mutation analysis. Protein Eng Des Sel 23:321–326. https://doi.org/10.1093/protein/gzp078
Duchêne DA, Duchêne S, Ho SYW (2017) New statistical criteria detect phylogenetic bias caused by compositional heterogeneity. Mol Biol Evol 34:1529–1534. https://doi.org/10.1093/molbev/msx092
Superson AA, Phelan D, Dekovich A, Battistuzzi FU (2019) Choice of species affects phylogenetic stability of deep nodes: an empirical example in Terrabacteria. Bioinformatics 35:3608–3616. https://doi.org/10.1093/bioinformatics/btz121
Townsend JP, Su Z, Tekle YI (2012) Phylogenetic signal and noise: predicting the power of a data set to resolve phylogeny. Syst Biol 61:835. https://doi.org/10.1093/sysbio/sys036
Shen XX, Hittinger CT, Rokas A (2017) Contentious relationships in phylogenomic studies can be driven by a handful of genes. Nat Ecol Evol 1:0126. https://doi.org/10.1038/s41559-017-0126
Mongiardino Koch N, Gauthier JA (2018) Noise and biases in genomic data may underlie radically different hypotheses for the position of Iguania within Squamata. PLoS One 13:e0202729. https://doi.org/10.1371/journal.pone.0202729
Rokas A, Carroll SB (2005) More genes or more taxa? The relative contribution of gene number and taxon number to phylogenetic accuracy. Mol Biol Evol 22:1337–1344. https://doi.org/10.1093/molbev/msi121
Sperling EA, Peterson KJ, Pisani D (2009) Phylogenetic-signal dissection of nuclear housekeeping genes supports the Paraphyly of sponges and the Monophyly of Eumetazoa. Mol Biol Evol 26:2261–2274. https://doi.org/10.1093/molbev/msp148
Kumar S, Filipski AJ, Battistuzzi FU et al (2012) Statistics and truth in phylogenomics. Mol Biol Evol 29:457–472. https://doi.org/10.1093/molbev/msr202
Pisani D, Pett W, Dohrmann M et al (2015) Genomic data do not support comb jellies as the sister group to all other animals. Proc Natl Acad Sci U S A 112:15402–15407. https://doi.org/10.1073/pnas.1518127112
Hejase HA, Liu KJ (2016) A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation. BMC Bioinformatics 17:422. https://doi.org/10.1186/s12859-016-1277-1
Fourment M, Magee AF, Whidden C et al (2020) 19 dubious ways to compute the marginal likelihood of a phylogenetic tree topology. Syst Biol 69:209–220. https://doi.org/10.1093/sysbio/syz046
Whidden C, Claywell BC, Fisher T et al (2020) Systematic exploration of the high likelihood set of phylogenetic tree topologies. Syst Biol 69:280–293. https://doi.org/10.1093/sysbio/syz047
Rodríguez A, Burgon JD, Lyra M et al (2017) Inferring the shallow phylogeny of true salamanders (Salamandra) by multiple phylogenomic approaches. Mol Phylogenet Evol 115:16–26. https://doi.org/10.1016/j.ympev.2017.07.009
Joyce J (2019) Bayes’ Theorem. In: Zalta EN (ed) The Stanford encyclopedia of philosophy, Spring 201. Metaphysics Research Lab, Stanford University
Venn J (1888) The logic of chance, 3rd edn. Macmillan, New York
Neyman J (1937) Outline of a theory of statistical estimation based on the classical theory of probability. Philos Trans R Soc London Ser A, Math Phys Sci 236:333–380. https://doi.org/10.1098/rsta.1937.0005
McCormack GP, Clewley JP (2002) The application of molecular phylogenetics to the analysis of viral genome diversity and evolution. Rev Med Virol 12:221–238. https://doi.org/10.1002/rmv.355
Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425. https://doi.org/10.1093/oxfordjournals.molbev.a040454
Sokal RR (1958) A statistical method for evaluating systematic relationships
Ané C, Larget B, Baum DA et al (2007) Bayesian estimation of concordance among gene trees. Mol Biol Evol 24:412–426. https://doi.org/10.1093/molbev/msl170
Drummond AJ, Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7:214. https://doi.org/10.1186/1471-2148-7-214
Ronquist F, Teslenko M, van der Mark P et al (2012) MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61:539–542. https://doi.org/10.1093/sysbio/sys029
Bouckaert R, Vaughan TG, Barido-Sottani J et al (2019) BEAST 2.5: an advanced software platform for Bayesian evolutionary analysis. PLoS Comput Biol 15:e1006650. https://doi.org/10.1371/journal.pcbi.1006650
Price MN, Dehal PS, Arkin AP (2009) FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 26:1641–1650. https://doi.org/10.1093/molbev/msp077
Price MN, Dehal PS, Arkin AP (2010) FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS One 5:e9490. https://doi.org/10.1371/journal.pone.0009490
Stamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312–1313. https://doi.org/10.1093/bioinformatics/btu033
Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ (2015) IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 32:268–274. https://doi.org/10.1093/molbev/msu300
Minh BQ, Schmidt HA, Chernomor O et al (2020) IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 37:1530–1534. https://doi.org/10.1093/molbev/msaa015
Hoang DT, Vinh LS, Flouri T et al (2018) MPBoot: fast phylogenetic maximum parsimony tree inference and bootstrap approximation. BMC Evol Biol 18:11. https://doi.org/10.1186/s12862-018-1131-3
Giribet G (2007) Efficient tree searches with available algorithms. Evol Bioinforma 3:341–356. https://doi.org/10.1177/117693430700300014
Sul SJ, Matthews S, Williams TL (2009) Using tree diversity to compare phylogenetic heuristics. BMC Bioinformatics 10:1–9. https://doi.org/10.1186/1471-2105-10-S4-S3
Davison A, Hinkley DV (1997) Bootstrap methods and their application. Cambridge University Press
Stamatakis A, Hoover P, Rougemont J (2008) A rapid bootstrap algorithm for the RAxML web servers. Syst Biol 57:758–771. https://doi.org/10.1080/10635150802429642
Nei M, Kumar S (2000) Molecular evolution and phylogenetics. Oxford University Press
Kapli P, Yang Z, Telford MJ (2020) Phylogenetic tree building in the genomic age. Nat Rev Genet 21:428–444. https://doi.org/10.1038/s41576-020-0233-0
Jukes TH, Cantor CR (1969) Evolution of protein molecules. In: Mammalian protein metabolism. Elsevier, pp 21–132
Dayhoff MO (1969) Atlas of protein sequence and structure. National Biomedical Research Foundation
Lanave C, Preparata G, Sacone C, Serio G (1984) A new method for calculating evolutionary substitution rates. J Mol Evol 20:86–93. https://doi.org/10.1007/BF02101990
Le SQ, Gascuel O (2008) An improved general amino acid replacement matrix. Mol Biol Evol 25:1307–1320. https://doi.org/10.1093/molbev/msn067
Gatto L, Catanzaro D, Milinkovitch MC (2006) Assessing the applicability of the GTR nucleotide substitution model through simulations. Evol Bioinforma 2:117693430600200. https://doi.org/10.1177/117693430600200020
Le SQ, Dang CC, Gascuel O (2012) Modeling protein evolution with several amino acid replacement matrices depending on site rates. Mol Biol Evol 29:2921–2936. https://doi.org/10.1093/molbev/mss112
Lopez P, Casane D, Philippe H (2002) Heterotachy, an important process of protein evolution. Mol Biol Evol 19:1–7. https://doi.org/10.1093/oxfordjournals.molbev.a003973
Lartillot N, Philippe H (2004) A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process. Mol Biol Evol 21:1095–1109. https://doi.org/10.1093/molbev/msh112
Pick KS, Philippe H, Schreiber F et al (2010) Improved phylogenomic taxon sampling noticeably affects Nonbilaterian relationships. Mol Biol Evol 27:1983–1987. https://doi.org/10.1093/molbev/msq089
Plazzi F, Ferrucci RR, Passamonti M (2010) Phylogenetic representativeness: a new method for evaluating taxon sampling in evolutionary studies. BMC Bioinformatics 11:209. https://doi.org/10.1186/1471-2105-11-209
Esselstyn JA, Oliveros CH, Swanson MT, Faircloth BC (2017) Investigating difficult nodes in the placental mammal tree with expanded taxon sampling and thousands of ultraconserved elements. Genome Biol Evol 9:2308–2321. https://doi.org/10.1093/gbe/evx168
Park DS, Worthington S, Xi Z (2018) Taxon sampling effects on the quantification and comparison of community phylogenetic diversity. Mol Ecol 27:1296–1308. https://doi.org/10.1111/mec.14520
Zou H, Jakovlić I, Zhang D et al (2020) Architectural instability, inverted skews and mitochondrial phylogenomics of Isopoda: outgroup choice affects the long-branch attraction artefacts. R Soc Open Sci 7:191887. https://doi.org/10.1098/rsos.191887
Mukherjee S, Stamatis D, Bertsch J et al (2019) Genomes OnLine database (GOLD) v.7: updates and new features. Nucleic Acids Res 47:D649–D659. https://doi.org/10.1093/nar/gky977
Mukherjee S, Stamatis D, Bertsch J et al (2021) Genomes OnLine Database (GOLD) v.8: overview and updates. Nucleic Acids Res 49:D723–D733. https://doi.org/10.1093/nar/gkaa983
Wheeler WC, Coddington JA, Crowley LM et al (2017) The spider tree of life: phylogeny of Araneae based on target-gene analyses from an extensive taxon sampling. Cladistics 33:574–616. https://doi.org/10.1111/cla.12182
Çıplak B, Yahyaoğlu Ö, Uluar O (2021) Revisiting Pholidopterini (Orthoptera, Tettigoniidae): Rapid radiation causes homoplasy and phylogenetic instability. Zool Scr 50:225–240. https://doi.org/10.1111/zsc.12463
Żyła D, Bogri A, Heath TA, Solodovnikov A (2021) Total-evidence analysis resolves the phylogenetic position of an enigmatic group of Paederinae rove beetles (Coleoptera: Staphylinidae). Mol Phylogenet Evol 157:107059. https://doi.org/10.1016/j.ympev.2020.107059
Linder CR, Suri R, Liu K, Warnow T (2010) Benchmark datasets and software for developing and testing methods for large-scale multiple sequence alignment and phylogenetic inference. PLoS Curr 2:RRN1195. https://doi.org/10.1371/currents.RRN1195
Didelot X, Croucher NJ, Bentley SD et al (2018) Bayesian inference of ancestral dates on bacterial phylogenetic trees. Nucleic Acids Res 46:e134–e134. https://doi.org/10.1093/nar/gky783
Lees JA, Kendall M, Parkhill J et al (2018) Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study. Wellcome Open Res 3:33. https://doi.org/10.12688/wellcomeopenres.14265.2
Wang Q (2019) Benchmarking and comparing software for phylogenetic analysis from genome-scale data
Li L (2003) OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res 13:2178–2189. https://doi.org/10.1101/gr.1224503
Chen F (2006) OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups. Nucleic Acids Res 34:D363–D368. https://doi.org/10.1093/nar/gkj123
Zerbino DR, Achuthan P, Akanni W et al (2018) Ensembl 2018. Nucleic Acids Res 46:D754–D761. https://doi.org/10.1093/nar/gkx1098
Lechner M, Findeiß S, Steiner L et al (2011) Proteinortho: detection of (Co-)orthologs in large-scale analysis. BMC Bioinformatics 12:124. https://doi.org/10.1186/1471-2105-12-124
Sonnhammer ELL, Östlund G (2015) InParanoid 8: orthology analysis between 273 proteomes, mostly eukaryotic. Nucleic Acids Res 43:D234–D239. https://doi.org/10.1093/nar/gku1203
Huerta-Cepas J, Szklarczyk D, Heller D et al (2019) eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res 47:D309–D314. https://doi.org/10.1093/nar/gky1085
Emms DM, Kelly S (2019) OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 20:238. https://doi.org/10.1186/s13059-019-1832-y
Notredame C, Higgins DG, Heringa J (2000) T-coffee: a novel method for fast and accurate multiple sequence alignment 1 1Edited by J. Thornton. J Mol Biol 302:205–217. https://doi.org/10.1006/jmbi.2000.4042
Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797. https://doi.org/10.1093/nar/gkh340
Sievers F, Higgins DG (2018) Clustal Omega for making accurate alignments of many protein sequences. Protein Sci 27:135–145. https://doi.org/10.1002/pro.3290
Katoh K, Rozewicki J, Yamada KD (2019) MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 20:1160–1166. https://doi.org/10.1093/bib/bbx108
de Queiroz A, Gatesy J (2007) The supermatrix approach to systematics. Trends Ecol Evol 22:34–41. https://doi.org/10.1016/j.tree.2006.10.002
Cotton JA, Wilkinson M (2009) Supertrees join the mainstream of phylogenetics. Trends Ecol Evol 24:1–3. https://doi.org/10.1016/j.tree.2008.08.006
Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24:1586–1591. https://doi.org/10.1093/molbev/msm088
Larget BR, Kotha SK, Dewey CN, Ané C (2010) BUCKy: gene tree/species tree reconciliation with Bayesian concordance analysis. Bioinformatics 26:2910–2911. https://doi.org/10.1093/bioinformatics/btq539
Wilson IJ, Weale ME, Balding DJ (2003) Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities. J R Stat Soc Ser A (Statistics Soc) 166:155–188. https://doi.org/10.1111/1467-985X.00264
Thomas GH, Hartmann K, Jetz W et al (2013) PASTIS: an R package to facilitate phylogenetic assembly with soft taxonomic inferences. Methods Ecol Evol 4:1011–1017. https://doi.org/10.1111/2041-210X.12117
Goloboff PA, Farris JS, Nixon KC (2008) TNT, a free program for phylogenetic analysis. Cladistics 24:774–786. https://doi.org/10.1111/j.1096-0031.2008.00217.x
Kumar S, Tamura K, Jakobsen IB, Nei M (2001) MEGA2: molecular evolutionary genetics analysis software. Bioinformatics 17:1244–1245. https://doi.org/10.1093/bioinformatics/17.12.1244
Kumar S, Stecher G, Tamura K (2016) MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 33:1870–1874. https://doi.org/10.1093/molbev/msw054
Kumar S, Stecher G, Li M et al (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547–1549. https://doi.org/10.1093/molbev/msy096
Swofford D (2002) PAUP*. phylogenetic analysis using parsimony (*and other methods). Version 4.0b10
Howe K, Bateman A, Durbin R (2002) QuickTree: building huge Neighbour-Joining trees of protein sequences. Bioinformatics 18:1546–1547. https://doi.org/10.1093/bioinformatics/18.11.1546
Vinh LS, Von Haeseler A (2004) IQPNNI: moving fast through tree space and stopping in time. Mol Biol Evol 21:1565–1571. https://doi.org/10.1093/molbev/msh176
Letunic I, Bork P (2019) Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res 47:W256–W259. https://doi.org/10.1093/nar/gkz239
James TY, Stajich JE, Hittinger CT, Rokas A (2020) Toward a fully resolved fungal tree of life. Annu Rev Microbiol 74:291–313. https://doi.org/10.1146/annurev-micro-022020-051835
Williams TA, Cox CJ, Foster PG et al (2020) Phylogenomics provides robust support for a two-domains tree of life. Nat Ecol Evol 4:138–147. https://doi.org/10.1038/s41559-019-1040-x
Camacho C, Coulouris G, Avagyan V et al (2009) BLAST+: architecture and applications. BMC Bioinformatics 10:421. https://doi.org/10.1186/1471-2105-10-421
Altschul SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215:403–410. https://doi.org/10.1016/S0022-2836(05)80360-2
Altschul SF, Madden TL, Schäffer AA et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402. https://doi.org/10.1093/nar/25.17.3389
Henikoff S, Henikoff JG (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci 89:10915–10919. https://doi.org/10.1073/pnas.89.22.10915
Buchfink B, Xie C, Huson DH (2015) Fast and sensitive protein alignment using DIAMOND. Nat Methods 12:59–60. https://doi.org/10.1038/nmeth.3176
Buchfink B, Reuter K, Drost H (2021) Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat Methods 18. https://doi.org/10.1038/s41592-021-01101-x
Robinson DF, Foulds LR (1981) Comparison of phylogenetic trees. Math Biosci 53:131–147. https://doi.org/10.1016/0025-5564(81)90043-2
Anisimova M, Gascuel O (2006) Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst Biol 55:539–552. https://doi.org/10.1080/10635150600755453
Shimodaira H, Hasegawa M (1999) Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol Biol Evol 16:1114–1116. https://doi.org/10.1093/oxfordjournals.molbev.a026201
Shimodaira H (2002) An approximately unbiased test of phylogenetic tree selection. Syst Biol 51:492–508. https://doi.org/10.1080/10635150290069913
Richards TA, Soanes DM, Foster PG et al (2009) Phylogenomic analysis demonstrates a pattern of rare and ancient horizontal gene transfer between plants and fungi. Plant Cell 21:1897–1911. https://doi.org/10.1105/tpc.109.065805
Leonard G, Soanes DM, Stevens JR (2011) Resolving the question of trypanosome monophyly: a comparative genomics approach using whole genome data sets with low taxon sampling. Infect Genet Evol 11:955–959. https://doi.org/10.1016/j.meegid.2011.03.005
Fang Y, Liu C, Lin J et al (2019) PhySpeTree: an automated pipeline for reconstructing phylogenetic species trees. BMC Evol Biol 19:219. https://doi.org/10.1186/s12862-019-1541-x
De Oliveira D, Ocaña KACS, Ogasawara E et al (2013) Performance evaluation of parallel strategies in public clouds: a study with phylogenomic workflows. Futur Gener Comput Syst 29:1816–1825. https://doi.org/10.1016/j.future.2012.12.019
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Powell, C.L.E., Battistuzzi, F.U. (2022). Testing Phylogenetic Stability with Variable Taxon Sampling. In: Luo, H. (eds) Environmental Microbial Evolution. Methods in Molecular Biology, vol 2569. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2691-7_8
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