ASTRAL statistics

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Citations per year

Number of citations per year for the bioinformatics software tool ASTRAL
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Tool usage distribution map

This map represents all the scientific publications referring to ASTRAL per scientific context
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Associated diseases

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Protocols

ASTRAL specifications

Information


Unique identifier OMICS_06055
Name ASTRAL
Alternative name Accurate Species TRee ALgorithm
Software type Application/Script, Package/Module
Interface Command line interface
Restrictions to use None
Input data Some trees.
Input format NEWICK
Output data A file providing the species tree topology, branch lengths in coalescent units, branch supports measured as local posterior probabilities and possible annotations with other quantities.
Output format NEWICK
Operating system Unix/Linux
Programming languages Java, Shell (Bash)
Computer skills Advanced
Version 5.6.1
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Tandy Warnow

Publications for Accurate Species TRee ALgorithm

ASTRAL citations

 (94)
library_books

Multiple origins of green blood in New Guinea lizards

2018
Sci Adv
PMCID: 5955620
PMID: 29774232
DOI: 10.1126/sciadv.aao5017

[…] d no support for Prasinohaema monophyly among more than 4000 individually estimated gene trees (tables S2 and S3) (). In addition, modeling for incomplete lineage sorting using a coalescent approach (ASTRAL) yielded topologies that were concordant with our unpartitioned ML approach (RAxML), indicating that our data were robust to problems of incomplete lineage sorting. Despite strong support for f […]

library_books

Heterogeneous rates of genome rearrangement contributed to the disparity of species richness in Ascomycota

2018
BMC Genomics
PMCID: 5937819
PMID: 29690866
DOI: 10.1186/s12864-018-4683-0

[…] th 100 bootstrap replicates [] under PROTGAMMAIJTTF model as recommended by ProtTest.3.4.2 []. Phylogenetic reconstruction was performed with all gene sets using the coalescence method implemented in ASTRAL v5.5.6 []. The genetic distance between two species was calculated based on the sequence alignment concatenated from the 160 alignments using PHYLIP [] with Jones-Taylor-Thornton (JTT) substitu […]

library_books

Practical considerations for plant phylogenomics

2018
Appl Plant Sci
PMCID: 5895195
PMID: 29732268
DOI: 10.1002/aps3.1038

[…] ments (e.g., see Johnson et al., ).Sequence alignments generated by target capture can be concatenated into a supermatrix or used for gene‐tree‐based methods of phylogenetic reconstruction, including ASTRAL‐III (Mirarab et al., ; Zhang et al., ), ASTRID (Vachaspati and Warnow, ), and BUCKy (Larget et al., ). This is especially useful with exon capture and Hyb‐Seq approaches, because loci are likel […]

library_books

Targeting legume loci: A comparison of three methods for target enrichment bait design in Leguminosae phylogenomics

2018
Appl Plant Sci
PMCID: 5895186
PMID: 29732266
DOI: 10.1002/aps3.1036

[…] For phylogeny estimation, we used a concatenation‐, partition‐based approach using maximum likelihood (CA‐ML) and two methods, ASTRAL (Mirarab and Warnow, ) and singular value decomposition quartets (SVDquartets; Chifman and Kubatko, ), that are statistically consistent under a coalescent process. To reconstruct the CA‐ML tre […]

library_books

Comparison of taxon‐specific versus general locus sets for targeted sequence capture in plant phylogenomics

2018
Appl Plant Sci
PMCID: 5895190
PMID: 29732262
DOI: 10.1002/aps3.1032

[…] with their greater average length and high proportion of variable sites, are also suited to the inference of well‐supported gene trees, which are necessary for a number of species tree methods (e.g., Accurate Species TRee ALgorithm [ASTRAL]; Mirarab and Warnow, ).Designing a general target locus set for a group does not require multiple genomic resources, but some source of genomic sequence data i […]

library_books

Testing for Polytomies in Phylogenetic Species Trees Using Quartet Frequencies

2018
Genes
PMCID: 5867853
PMID: 29495636
DOI: 10.3390/genes9030132

[…] ene trees was to reduce the gene tree estimation error. Alternatively, one can simply remove branches with support at or below a certain threshold in gene trees and use the resulting tree as input to ASTRAL []. With this procedure and the support threshold set to 10%, we generated a new ASTRAL tree based on all 14,446 unbinned gene trees from the avian dataset [,] (b). The resulting tree was large […]


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ASTRAL institution(s)
Department of Electrical and Computer Engineering, University of California at San Diego, Gilman Drive, La Jolla, CA, USA; Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology, University of California at San Diego, La Jolla, CA, USA
ASTRAL funding source(s)
Supported by the National Science Foundation grant IIS-1565862 and the NSF grant ACI-1053575.

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