MAST: Phylogenetic Inference with Mixtures Across Sites and Trees Article Swipe
Thomas K. F. Wong
,
Caitlin Cherryh
,
Allen G. Rodrigo
,
Matthew W. Hahn
,
Bùi Quang Minh
,
Robert Lanfear
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.10.06.511210
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.10.06.511210
Hundreds or thousands of loci are now routinely used in modern phylogenomic studies. Concatenation approaches to tree inference assume that there is a single topology for the entire dataset, but different loci may have different evolutionary histories due to incomplete lineage sorting, introgression, and/or horizontal gene transfer; even single loci may not be treelike due to recombination. To overcome this shortcoming, we introduce the mixture across sites and trees (MAST) model, which uses a mixture of bifurcating trees to represent multiple histories in a single concatenated alignment. The MAST model allows each tree to have its own topology, branch lengths, substitution model, nucleotide or amino acid frequencies, and model of rate heterogeneity across sites. We implemented the MAST model in a maximum-likelihood framework in the popular phylogenetic software, IQ-TREE. Simulations show that we can accurately recover the true model parameters, including branch lengths and tree weights (i.e. frequencies) for a given set of tree topologies. We also show that we can use standard statistical inference approaches to reject a single-tree model when data are simulated under multiple trees (and vice versa). We applied the MAST model to multiple primate datasets and found that it can recover the signal of incomplete lineage sorting in the Great Apes, as well as the asymmetry in minor trees caused by introgression among several macaque species. When applied to a dataset of four Platyrrhine species for which standard concatenated maximum likelihood and gene tree approaches disagree, we find that MAST gives the highest weight to the tree favored by gene tree approaches. These results suggest that the MAST model is able to analyse a concatenated alignment using maximum likelihood, while avoiding some of the biases that come with assuming there is only a single tree. The MAST model can therefore offer unique biological insights when applied to datasets with multiple evolutionary histories. We discuss how it can be extended in the future.
Related Topics
Concepts
Coalescent theory
Phylogenetic tree
Tree rearrangement
Tree (set theory)
Inference
Computer science
Biology
Algorithm
Mathematics
Evolutionary biology
Computational biology
Artificial intelligence
Combinatorics
Genetics
Gene
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2022.10.06.511210
- OA Status
- green
- Cited By
- 7
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4303672044
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4303672044Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2022.10.06.511210Digital Object Identifier
- Title
-
MAST: Phylogenetic Inference with Mixtures Across Sites and TreesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-10-08Full publication date if available
- Authors
-
Thomas K. F. Wong, Caitlin Cherryh, Allen G. Rodrigo, Matthew W. Hahn, Bùi Quang Minh, Robert LanfearList of authors in order
- Landing page
-
https://doi.org/10.1101/2022.10.06.511210Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1101/2022.10.06.511210Direct OA link when available
- Concepts
-
Coalescent theory, Phylogenetic tree, Tree rearrangement, Tree (set theory), Inference, Computer science, Biology, Algorithm, Mathematics, Evolutionary biology, Computational biology, Artificial intelligence, Combinatorics, Genetics, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 4, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4303672044 |
|---|---|
| doi | https://doi.org/10.1101/2022.10.06.511210 |
| ids.doi | https://doi.org/10.1101/2022.10.06.511210 |
| ids.openalex | https://openalex.org/W4303672044 |
| fwci | 0.86148411 |
| type | preprint |
| title | MAST: Phylogenetic Inference with Mixtures Across Sites and Trees |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10015 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.9991000294685364 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1312 |
| topics[0].subfield.display_name | Molecular Biology |
| topics[0].display_name | Genomics and Phylogenetic Studies |
| topics[1].id | https://openalex.org/T10012 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9983999729156494 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1311 |
| topics[1].subfield.display_name | Genetics |
| topics[1].display_name | Genetic diversity and population structure |
| topics[2].id | https://openalex.org/T11468 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9958999752998352 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1311 |
| topics[2].subfield.display_name | Genetics |
| topics[2].display_name | Genetic Mapping and Diversity in Plants and Animals |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2554327 |
| concepts[0].level | 4 |
| concepts[0].score | 0.8652400970458984 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2698599 |
| concepts[0].display_name | Coalescent theory |
| concepts[1].id | https://openalex.org/C193252679 |
| concepts[1].level | 3 |
| concepts[1].score | 0.683152437210083 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q242125 |
| concepts[1].display_name | Phylogenetic tree |
| concepts[2].id | https://openalex.org/C53208351 |
| concepts[2].level | 4 |
| concepts[2].score | 0.5476606488227844 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q7837630 |
| concepts[2].display_name | Tree rearrangement |
| concepts[3].id | https://openalex.org/C113174947 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5465219020843506 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2859736 |
| concepts[3].display_name | Tree (set theory) |
| concepts[4].id | https://openalex.org/C2776214188 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5182318687438965 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q408386 |
| concepts[4].display_name | Inference |
| concepts[5].id | https://openalex.org/C41008148 |
| concepts[5].level | 0 |
| concepts[5].score | 0.4296310544013977 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[5].display_name | Computer science |
| concepts[6].id | https://openalex.org/C86803240 |
| concepts[6].level | 0 |
| concepts[6].score | 0.4016653597354889 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[6].display_name | Biology |
| concepts[7].id | https://openalex.org/C11413529 |
| concepts[7].level | 1 |
| concepts[7].score | 0.3341901898384094 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[7].display_name | Algorithm |
| concepts[8].id | https://openalex.org/C33923547 |
| concepts[8].level | 0 |
| concepts[8].score | 0.332643985748291 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[8].display_name | Mathematics |
| concepts[9].id | https://openalex.org/C78458016 |
| concepts[9].level | 1 |
| concepts[9].score | 0.33096957206726074 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q840400 |
| concepts[9].display_name | Evolutionary biology |
| concepts[10].id | https://openalex.org/C70721500 |
| concepts[10].level | 1 |
| concepts[10].score | 0.3218437433242798 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q177005 |
| concepts[10].display_name | Computational biology |
| concepts[11].id | https://openalex.org/C154945302 |
| concepts[11].level | 1 |
| concepts[11].score | 0.3050178289413452 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[11].display_name | Artificial intelligence |
| concepts[12].id | https://openalex.org/C114614502 |
| concepts[12].level | 1 |
| concepts[12].score | 0.18700334429740906 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q76592 |
| concepts[12].display_name | Combinatorics |
| concepts[13].id | https://openalex.org/C54355233 |
| concepts[13].level | 1 |
| concepts[13].score | 0.17078116536140442 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7162 |
| concepts[13].display_name | Genetics |
| concepts[14].id | https://openalex.org/C104317684 |
| concepts[14].level | 2 |
| concepts[14].score | 0.14632582664489746 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[14].display_name | Gene |
| keywords[0].id | https://openalex.org/keywords/coalescent-theory |
| keywords[0].score | 0.8652400970458984 |
| keywords[0].display_name | Coalescent theory |
| keywords[1].id | https://openalex.org/keywords/phylogenetic-tree |
| keywords[1].score | 0.683152437210083 |
| keywords[1].display_name | Phylogenetic tree |
| keywords[2].id | https://openalex.org/keywords/tree-rearrangement |
| keywords[2].score | 0.5476606488227844 |
| keywords[2].display_name | Tree rearrangement |
| keywords[3].id | https://openalex.org/keywords/tree |
| keywords[3].score | 0.5465219020843506 |
| keywords[3].display_name | Tree (set theory) |
| keywords[4].id | https://openalex.org/keywords/inference |
| keywords[4].score | 0.5182318687438965 |
| keywords[4].display_name | Inference |
| keywords[5].id | https://openalex.org/keywords/computer-science |
| keywords[5].score | 0.4296310544013977 |
| keywords[5].display_name | Computer science |
| keywords[6].id | https://openalex.org/keywords/biology |
| keywords[6].score | 0.4016653597354889 |
| keywords[6].display_name | Biology |
| keywords[7].id | https://openalex.org/keywords/algorithm |
| keywords[7].score | 0.3341901898384094 |
| keywords[7].display_name | Algorithm |
| keywords[8].id | https://openalex.org/keywords/mathematics |
| keywords[8].score | 0.332643985748291 |
| keywords[8].display_name | Mathematics |
| keywords[9].id | https://openalex.org/keywords/evolutionary-biology |
| keywords[9].score | 0.33096957206726074 |
| keywords[9].display_name | Evolutionary biology |
| keywords[10].id | https://openalex.org/keywords/computational-biology |
| keywords[10].score | 0.3218437433242798 |
| keywords[10].display_name | Computational biology |
| keywords[11].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[11].score | 0.3050178289413452 |
| keywords[11].display_name | Artificial intelligence |
| keywords[12].id | https://openalex.org/keywords/combinatorics |
| keywords[12].score | 0.18700334429740906 |
| keywords[12].display_name | Combinatorics |
| keywords[13].id | https://openalex.org/keywords/genetics |
| keywords[13].score | 0.17078116536140442 |
| keywords[13].display_name | Genetics |
| keywords[14].id | https://openalex.org/keywords/gene |
| keywords[14].score | 0.14632582664489746 |
| keywords[14].display_name | Gene |
| language | en |
| locations[0].id | doi:10.1101/2022.10.06.511210 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306402567 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| locations[0].source.host_organization | https://openalex.org/I2750212522 |
| locations[0].source.host_organization_name | Cold Spring Harbor Laboratory |
| locations[0].source.host_organization_lineage | https://openalex.org/I2750212522 |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/2022.10.06.511210 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5091416583 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-0580-6324 |
| authorships[0].author.display_name | Thomas K. F. Wong |
| authorships[0].countries | AU |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I118347636 |
| authorships[0].affiliations[0].raw_affiliation_string | Research School of Biology, Australian National University, Australian Capital Territory, Australia |
| authorships[0].institutions[0].id | https://openalex.org/I118347636 |
| authorships[0].institutions[0].ror | https://ror.org/019wvm592 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I118347636 |
| authorships[0].institutions[0].country_code | AU |
| authorships[0].institutions[0].display_name | Australian National University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Thomas KF Wong |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Research School of Biology, Australian National University, Australian Capital Territory, Australia |
| authorships[1].author.id | https://openalex.org/A5076701984 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6146-4376 |
| authorships[1].author.display_name | Caitlin Cherryh |
| authorships[1].countries | AU |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I118347636 |
| authorships[1].affiliations[0].raw_affiliation_string | Research School of Biology, Australian National University, Australian Capital Territory, Australia |
| authorships[1].institutions[0].id | https://openalex.org/I118347636 |
| authorships[1].institutions[0].ror | https://ror.org/019wvm592 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I118347636 |
| authorships[1].institutions[0].country_code | AU |
| authorships[1].institutions[0].display_name | Australian National University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Caitlin Cherryh |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Research School of Biology, Australian National University, Australian Capital Territory, Australia |
| authorships[2].author.id | https://openalex.org/A5015045944 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-8327-7317 |
| authorships[2].author.display_name | Allen G. Rodrigo |
| authorships[2].countries | NZ |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I154130895 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Biological Sciences, University of Auckland, Auckland, New Zealand |
| authorships[2].institutions[0].id | https://openalex.org/I154130895 |
| authorships[2].institutions[0].ror | https://ror.org/03b94tp07 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I154130895 |
| authorships[2].institutions[0].country_code | NZ |
| authorships[2].institutions[0].display_name | University of Auckland |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Allen G Rodrigo |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Biological Sciences, University of Auckland, Auckland, New Zealand |
| authorships[3].author.id | https://openalex.org/A5038671526 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-5731-8808 |
| authorships[3].author.display_name | Matthew W. Hahn |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210119109 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Biology and Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America |
| authorships[3].institutions[0].id | https://openalex.org/I4210119109 |
| authorships[3].institutions[0].ror | https://ror.org/02k40bc56 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210119109, https://openalex.org/I592451 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Indiana University Bloomington |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Matthew W Hahn |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Biology and Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America |
| authorships[4].author.id | https://openalex.org/A5019880902 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-5535-6560 |
| authorships[4].author.display_name | Bùi Quang Minh |
| authorships[4].countries | AU |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I118347636 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Computing, Australian National University, Australian Capital Territory, Australia |
| authorships[4].institutions[0].id | https://openalex.org/I118347636 |
| authorships[4].institutions[0].ror | https://ror.org/019wvm592 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I118347636 |
| authorships[4].institutions[0].country_code | AU |
| authorships[4].institutions[0].display_name | Australian National University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Bui Quang Minh |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | School of Computing, Australian National University, Australian Capital Territory, Australia |
| authorships[5].author.id | https://openalex.org/A5037983874 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-1140-2596 |
| authorships[5].author.display_name | Robert Lanfear |
| authorships[5].countries | AU |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I118347636 |
| authorships[5].affiliations[0].raw_affiliation_string | Research School of Biology, Australian National University, Australian Capital Territory, Australia |
| authorships[5].institutions[0].id | https://openalex.org/I118347636 |
| authorships[5].institutions[0].ror | https://ror.org/019wvm592 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I118347636 |
| authorships[5].institutions[0].country_code | AU |
| authorships[5].institutions[0].display_name | Australian National University |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Robert Lanfear |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Research School of Biology, Australian National University, Australian Capital Territory, Australia |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1101/2022.10.06.511210 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | MAST: Phylogenetic Inference with Mixtures Across Sites and Trees |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10015 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.9991000294685364 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1312 |
| primary_topic.subfield.display_name | Molecular Biology |
| primary_topic.display_name | Genomics and Phylogenetic Studies |
| related_works | https://openalex.org/W1892960895, https://openalex.org/W85430217, https://openalex.org/W1553205505, https://openalex.org/W4205930990, https://openalex.org/W1993799876, https://openalex.org/W2917424786, https://openalex.org/W2362218761, https://openalex.org/W2113708670, https://openalex.org/W2158340599, https://openalex.org/W2062354928 |
| cited_by_count | 7 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 4 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1101/2022.10.06.511210 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306402567 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| best_oa_location.source.host_organization | https://openalex.org/I2750212522 |
| best_oa_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.1101/2022.10.06.511210 |
| primary_location.id | doi:10.1101/2022.10.06.511210 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306402567 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| primary_location.source.host_organization | https://openalex.org/I2750212522 |
| primary_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| primary_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/2022.10.06.511210 |
| publication_date | 2022-10-08 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2141052558, https://openalex.org/W2111211467, https://openalex.org/W2146058063, https://openalex.org/W2901954177, https://openalex.org/W2787520586, https://openalex.org/W1996835973, https://openalex.org/W2161973008, https://openalex.org/W2118488195, https://openalex.org/W1966971981, https://openalex.org/W2145608399, https://openalex.org/W2131961145, https://openalex.org/W2037654474, https://openalex.org/W2139050004, https://openalex.org/W2801361050, https://openalex.org/W2125024684, https://openalex.org/W2046132104, https://openalex.org/W2107608009, https://openalex.org/W2950847777, https://openalex.org/W2952113249, https://openalex.org/W2753562621, https://openalex.org/W2952712909, https://openalex.org/W2883170162, https://openalex.org/W2124790653, https://openalex.org/W2147307434, https://openalex.org/W2100030044, https://openalex.org/W2966384155, https://openalex.org/W2111647009, https://openalex.org/W1593676244, https://openalex.org/W2102424972, https://openalex.org/W2009435671, https://openalex.org/W2049633694, https://openalex.org/W4229066198, https://openalex.org/W2134599124, https://openalex.org/W1975933692, https://openalex.org/W3107762183, https://openalex.org/W2168852102, https://openalex.org/W2127713506, https://openalex.org/W2052432722, https://openalex.org/W2949247626, https://openalex.org/W2962845623, https://openalex.org/W1988024444, https://openalex.org/W2126044526, https://openalex.org/W2289619055, https://openalex.org/W4230670946, https://openalex.org/W2124362779, https://openalex.org/W1977169047, https://openalex.org/W2067214353 |
| referenced_works_count | 47 |
| abstract_inverted_index.a | 22, 73, 83, 120, 149, 168, 224, 268, 287 |
| abstract_inverted_index.To | 57 |
| abstract_inverted_index.We | 114, 155, 181, 307 |
| abstract_inverted_index.as | 206, 208 |
| abstract_inverted_index.be | 52, 312 |
| abstract_inverted_index.by | 215, 253 |
| abstract_inverted_index.in | 9, 82, 119, 123, 202, 211, 314 |
| abstract_inverted_index.is | 21, 264, 285 |
| abstract_inverted_index.it | 193, 310 |
| abstract_inverted_index.of | 3, 75, 109, 152, 198, 226, 277 |
| abstract_inverted_index.or | 1, 103 |
| abstract_inverted_index.to | 15, 38, 55, 78, 93, 166, 186, 223, 249, 266, 301 |
| abstract_inverted_index.we | 61, 132, 159, 241 |
| abstract_inverted_index.The | 87, 290 |
| abstract_inverted_index.and | 67, 107, 143, 190, 236 |
| abstract_inverted_index.are | 5, 173 |
| abstract_inverted_index.but | 29 |
| abstract_inverted_index.can | 133, 160, 194, 293, 311 |
| abstract_inverted_index.due | 37, 54 |
| abstract_inverted_index.for | 25, 148, 230 |
| abstract_inverted_index.how | 309 |
| abstract_inverted_index.its | 95 |
| abstract_inverted_index.may | 32, 50 |
| abstract_inverted_index.not | 51 |
| abstract_inverted_index.now | 6 |
| abstract_inverted_index.own | 96 |
| abstract_inverted_index.set | 151 |
| abstract_inverted_index.the | 26, 63, 116, 124, 136, 183, 196, 203, 209, 246, 250, 261, 278, 315 |
| abstract_inverted_index.use | 161 |
| abstract_inverted_index.(and | 178 |
| abstract_inverted_index.MAST | 88, 117, 184, 244, 262, 291 |
| abstract_inverted_index.When | 221 |
| abstract_inverted_index.able | 265 |
| abstract_inverted_index.acid | 105 |
| abstract_inverted_index.also | 156 |
| abstract_inverted_index.come | 281 |
| abstract_inverted_index.data | 172 |
| abstract_inverted_index.each | 91 |
| abstract_inverted_index.even | 47 |
| abstract_inverted_index.find | 242 |
| abstract_inverted_index.four | 227 |
| abstract_inverted_index.gene | 45, 237, 254 |
| abstract_inverted_index.have | 33, 94 |
| abstract_inverted_index.loci | 4, 31, 49 |
| abstract_inverted_index.only | 286 |
| abstract_inverted_index.rate | 110 |
| abstract_inverted_index.show | 130, 157 |
| abstract_inverted_index.some | 276 |
| abstract_inverted_index.that | 19, 131, 158, 192, 243, 260, 280 |
| abstract_inverted_index.this | 59 |
| abstract_inverted_index.tree | 16, 92, 144, 153, 238, 251, 255 |
| abstract_inverted_index.true | 137 |
| abstract_inverted_index.used | 8 |
| abstract_inverted_index.uses | 72 |
| abstract_inverted_index.vice | 179 |
| abstract_inverted_index.well | 207 |
| abstract_inverted_index.when | 171, 299 |
| abstract_inverted_index.with | 282, 303 |
| abstract_inverted_index.(i.e. | 146 |
| abstract_inverted_index.Apes, | 205 |
| abstract_inverted_index.Great | 204 |
| abstract_inverted_index.These | 257 |
| abstract_inverted_index.amino | 104 |
| abstract_inverted_index.among | 217 |
| abstract_inverted_index.found | 191 |
| abstract_inverted_index.given | 150 |
| abstract_inverted_index.gives | 245 |
| abstract_inverted_index.minor | 212 |
| abstract_inverted_index.model | 89, 108, 118, 138, 170, 185, 263, 292 |
| abstract_inverted_index.offer | 295 |
| abstract_inverted_index.sites | 66 |
| abstract_inverted_index.there | 20, 284 |
| abstract_inverted_index.tree. | 289 |
| abstract_inverted_index.trees | 68, 77, 177, 213 |
| abstract_inverted_index.under | 175 |
| abstract_inverted_index.using | 271 |
| abstract_inverted_index.which | 71, 231 |
| abstract_inverted_index.while | 274 |
| abstract_inverted_index.(MAST) | 69 |
| abstract_inverted_index.across | 65, 112 |
| abstract_inverted_index.allows | 90 |
| abstract_inverted_index.and/or | 43 |
| abstract_inverted_index.assume | 18 |
| abstract_inverted_index.biases | 279 |
| abstract_inverted_index.branch | 98, 141 |
| abstract_inverted_index.caused | 214 |
| abstract_inverted_index.entire | 27 |
| abstract_inverted_index.model, | 70, 101 |
| abstract_inverted_index.modern | 10 |
| abstract_inverted_index.reject | 167 |
| abstract_inverted_index.signal | 197 |
| abstract_inverted_index.single | 23, 48, 84, 288 |
| abstract_inverted_index.sites. | 113 |
| abstract_inverted_index.unique | 296 |
| abstract_inverted_index.weight | 248 |
| abstract_inverted_index.analyse | 267 |
| abstract_inverted_index.applied | 182, 222, 300 |
| abstract_inverted_index.dataset | 225 |
| abstract_inverted_index.discuss | 308 |
| abstract_inverted_index.favored | 252 |
| abstract_inverted_index.future. | 316 |
| abstract_inverted_index.highest | 247 |
| abstract_inverted_index.lengths | 142 |
| abstract_inverted_index.lineage | 40, 200 |
| abstract_inverted_index.macaque | 219 |
| abstract_inverted_index.maximum | 234, 272 |
| abstract_inverted_index.mixture | 64, 74 |
| abstract_inverted_index.popular | 125 |
| abstract_inverted_index.primate | 188 |
| abstract_inverted_index.recover | 135, 195 |
| abstract_inverted_index.results | 258 |
| abstract_inverted_index.several | 218 |
| abstract_inverted_index.sorting | 201 |
| abstract_inverted_index.species | 229 |
| abstract_inverted_index.suggest | 259 |
| abstract_inverted_index.versa). | 180 |
| abstract_inverted_index.weights | 145 |
| abstract_inverted_index.Hundreds | 0 |
| abstract_inverted_index.IQ-TREE. | 128 |
| abstract_inverted_index.assuming | 283 |
| abstract_inverted_index.avoiding | 275 |
| abstract_inverted_index.dataset, | 28 |
| abstract_inverted_index.datasets | 189, 302 |
| abstract_inverted_index.extended | 313 |
| abstract_inverted_index.insights | 298 |
| abstract_inverted_index.lengths, | 99 |
| abstract_inverted_index.multiple | 80, 176, 187, 304 |
| abstract_inverted_index.overcome | 58 |
| abstract_inverted_index.sorting, | 41 |
| abstract_inverted_index.species. | 220 |
| abstract_inverted_index.standard | 162, 232 |
| abstract_inverted_index.studies. | 12 |
| abstract_inverted_index.topology | 24 |
| abstract_inverted_index.treelike | 53 |
| abstract_inverted_index.alignment | 270 |
| abstract_inverted_index.asymmetry | 210 |
| abstract_inverted_index.different | 30, 34 |
| abstract_inverted_index.disagree, | 240 |
| abstract_inverted_index.framework | 122 |
| abstract_inverted_index.histories | 36, 81 |
| abstract_inverted_index.including | 140 |
| abstract_inverted_index.inference | 17, 164 |
| abstract_inverted_index.introduce | 62 |
| abstract_inverted_index.represent | 79 |
| abstract_inverted_index.routinely | 7 |
| abstract_inverted_index.simulated | 174 |
| abstract_inverted_index.software, | 127 |
| abstract_inverted_index.therefore | 294 |
| abstract_inverted_index.thousands | 2 |
| abstract_inverted_index.topology, | 97 |
| abstract_inverted_index.transfer; | 46 |
| abstract_inverted_index.accurately | 134 |
| abstract_inverted_index.alignment. | 86 |
| abstract_inverted_index.approaches | 14, 165, 239 |
| abstract_inverted_index.biological | 297 |
| abstract_inverted_index.histories. | 306 |
| abstract_inverted_index.horizontal | 44 |
| abstract_inverted_index.incomplete | 39, 199 |
| abstract_inverted_index.likelihood | 235 |
| abstract_inverted_index.nucleotide | 102 |
| abstract_inverted_index.Platyrrhine | 228 |
| abstract_inverted_index.Simulations | 129 |
| abstract_inverted_index.approaches. | 256 |
| abstract_inverted_index.bifurcating | 76 |
| abstract_inverted_index.implemented | 115 |
| abstract_inverted_index.likelihood, | 273 |
| abstract_inverted_index.parameters, | 139 |
| abstract_inverted_index.single-tree | 169 |
| abstract_inverted_index.statistical | 163 |
| abstract_inverted_index.topologies. | 154 |
| abstract_inverted_index.concatenated | 85, 233, 269 |
| abstract_inverted_index.evolutionary | 35, 305 |
| abstract_inverted_index.frequencies) | 147 |
| abstract_inverted_index.frequencies, | 106 |
| abstract_inverted_index.phylogenetic | 126 |
| abstract_inverted_index.phylogenomic | 11 |
| abstract_inverted_index.shortcoming, | 60 |
| abstract_inverted_index.substitution | 100 |
| abstract_inverted_index.Concatenation | 13 |
| abstract_inverted_index.heterogeneity | 111 |
| abstract_inverted_index.introgression | 216 |
| abstract_inverted_index.introgression, | 42 |
| abstract_inverted_index.recombination. | 56 |
| abstract_inverted_index.maximum-likelihood | 121 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5091416583 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I118347636 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.67090898 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |