scholarly journals IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era

2019 ◽  
Author(s):  
Bui Quang Minh ◽  
Heiko Schmidt ◽  
Olga Chernomor ◽  
Dominik Schrempf ◽  
Michael Woodhams ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Software Package ◽  
Genomic Data ◽  
Phylogenetic Inference ◽  
Sequence Evolution ◽  
Computational Approaches ◽  
Link Type ◽  
New Models ◽  
User Friendly

AbstractIQ-TREE (http://www.iqtree.org) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

scholarly journals IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

2020 ◽  
Vol 37 (5) ◽  
pp. 1530-1534 ◽  
Author(s):  
Bui Quang Minh ◽  
Heiko A Schmidt ◽  
Olga Chernomor ◽  
Dominik Schrempf ◽  
Michael D Woodhams ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Software Package ◽  
Genomic Data ◽  
Phylogenetic Inference ◽  
Sequence Evolution ◽  
Computational Approaches ◽  
New Models ◽  
User Friendly

Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

scholarly journals cognac: rapid generation of concatenated gene alignments for phylogenetic inference from large whole genome sequencing datasets

2020 ◽  
Author(s):  
Ryan D. Crawford ◽  
Evan S. Snitkin
Keyword(s):  
Phylogenetic Analysis ◽  
Genome Sequencing ◽  
Software Package ◽  
Genomic Data ◽  
Phylogenetic Inference ◽  
R Package ◽  
Core Gene ◽  
Whole Genome ◽  
Rapid Generation ◽  
User Friendly

AbstractThe quantity of genomic data is expanding at an increasing rate. Tools for phylogenetic analysis which scale to the quantity of available data are required. We present cognac, a user-friendly software package to rapidly generate concatenated gene alignments for phylogenetic analysis. We applied this tool to generate core gene alignments for very large genomic datasets, including a dataset of over 11,000 genomes from the genus Escherichia containing 1,353 genes, which was constructed in less than 17 hours. We have released cognac as an R package (https://github.com/rdcrawford/cognac) with customizable parameters for adaptation to diverse applications.

scholarly journals The Prevalence and Impact of Model Violations in Phylogenetics Analysis

2018 ◽  
Author(s):  
Suha Naser-Khdour ◽  
Bui Quang Minh ◽  
Wenqi Zhang ◽  
Eric Stone ◽  
Robert Lanfear
Keyword(s):  
Phylogenetic Inference ◽  
Sequence Evolution ◽  
Matched Pairs ◽  
Tree Reconstruction ◽  
Link Type ◽  
Tree Topologies ◽  
Phylogenetics Analysis

AbstractIn phylogenetic inference we commonly use models of substitution which assume that sequence evolution is stationary, reversible and homogeneous (SRH). Although the use of such models is often criticized, the extent of SRH violations and their effects on phylogenetic inference of tree topologies and edge lengths are not well understood. Here, we introduce and apply the maximal matched-pairs tests of homogeneity to assess the scale and impact of SRH model violations on 3,572 partitions from 35 published phylogenetic datasets. We show that many partitions (39.5%) reject the SRH assumptions, and that for most datasets, the topologies of trees inferred from all partitions differ significantly from those inferred using the subset of partitions that do not reject the SRH assumptions. These results suggest that the extent and effects of model violation in phylogenetics may be substantial. They highlight the importance of testing for model violations and possibly excluding partitions that violate models prior to tree reconstruction. They also suggest that further effort in developing models that do not require SRH assumptions could lead to large improvements in the accuracy of phylogenomic inference. The scripts necessary to perform the analysis are available in https://github.com/roblanf/SRHtests, and the new tests we describe are available as a new option in IQ-TREE (http://www.iqtree.org).

scholarly journals UFBoot2: Improving the Ultrafast Bootstrap Approximation

2017 ◽  
Author(s):  
Diep Thi Hoang ◽  
Olga Chernomor ◽  
Arndt von Haeseler ◽  
Bui Quang Minh ◽  
Le Sy Vinh
Keyword(s):  
Maximum Likelihood ◽  
Software Package ◽  
Phylogenetic Analyses ◽  
Computing Time ◽  
Bootstrap Resampling ◽  
Bootstrap Approximation ◽  
Link Type ◽  
Efficient Alternative ◽  
Computationally Intensive

AbstractThe standard bootstrap (SBS), despite being computationally intensive, is widely used in maximum likelihood phylogenetic analyses. We recently proposed the ultrafast bootstrap approximation (UFBoot) to reduce computing time while achieving more unbiased branch supports than SBS under mild model violations. UFBoot has been steadily adopted as an efficient alternative to SBS and other bootstrap approaches.Here, we present UFBoot2, which substantially accelerates UFBoot and reduces the risk of overestimating branch supports due to polytomies or severe model violations. Additionally, UFBoot2 provides suitable bootstrap resampling strategies for phylogenomic data. UFBoot2 is 778 and 8.4 times (median) faster than SBS and RAxML rapid bootstrap on tested datasets, respectively. UFBoot2 is implemented in the IQ-TREE software package version 1.6 and freely available at http://www.iqtree.org.

scholarly journals RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference

2019 ◽  
Vol 35 (21) ◽  
pp. 4453-4455 ◽  
Author(s):  
Alexey M Kozlov ◽  
Diego Darriba ◽  
Tomáš Flouri ◽  
Benoit Morel ◽  
Alexandros Stamatakis
Keyword(s):  
Maximum Likelihood ◽  
Search Algorithm ◽  
Phylogenetic Inference ◽  
Supplementary Information ◽  
Biological Research ◽  
Bootstrap Support ◽  
Optimal Tree ◽  
User Friendly ◽  
Tree Search Algorithm ◽  
Improved Accuracy

Abstract Motivation Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets. Results We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML-NG offers improved accuracy, flexibility, speed, scalability, and usability compared with RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and the recently introduced transfer bootstrap support metric. Availability and implementation The code is available under GNU GPL at https://github.com/amkozlov/raxml-ng. RAxML-NG web service (maintained by Vital-IT) is available at https://raxml-ng.vital-it.ch/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals RAxML-NG: A fast, scalable, and user-friendly tool for maximum likelihood phylogenetic inference

2018 ◽  
Author(s):  
Alexey M. Kozlov ◽  
Diego Darriba ◽  
Tomáš Flouri ◽  
Benoit Morel ◽  
Alexandros Stamatakis
Keyword(s):  
Search Algorithm ◽  
Phylogenetic Inference ◽  
Biological Research ◽  
Bootstrap Support ◽  
Link Type ◽  
Optimal Tree ◽  
Tree Space ◽  
User Friendly ◽  
Tree Search Algorithm ◽  
Improved Accuracy

AbstractMotivationPhylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture, and medicine. Finding the optimal tree under the popular maximum like-lihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets.ResultsWe present RAxML-NG, a from scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML- NG offers improved accuracy, flexibility, speed, scalability, and usability compared to RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and a the recently introduced transfer bootstrap support metric.AvailabilityThe code is available under GNU GPL at https://github.com/amkozlov/raxml-ng.RAxML-NG web service (maintained by Vital- IT) is available at https://raxml-ng.vital-it.ch/[email protected]

scholarly journals cognac: rapid generation of concatenated gene alignments for phylogenetic inference from large, bacterial whole genome sequencing datasets

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ryan D. Crawford ◽  
Evan S. Snitkin
Keyword(s):  
Phylogenetic Analysis ◽  
Software Package ◽  
Phylogenetic Inference ◽  
R Package ◽  
Core Gene ◽  
Data Driven ◽  
Marker Genes ◽  
Data Driven Approach ◽  
Rapid Generation ◽  
User Friendly

Abstract Background The quantity of genomic data is expanding at an increasing rate. Tools for phylogenetic analysis which scale to the quantity of available data are required. To address this need, we present cognac, a user-friendly software package to rapidly generate concatenated gene alignments for phylogenetic analysis. Results We illustrate that cognac is able to rapidly identify phylogenetic marker genes using a data driven approach and efficiently generate concatenated gene alignments for very large genomic datasets. To benchmark our tool, we generated core gene alignments for eight unique genera of bacteria, including a dataset of over 11,000 genomes from the genus Escherichia producing an alignment with 1353 genes, which was constructed in less than 17 h. Conclusions We demonstrate that cognac presents an efficient method for generating concatenated gene alignments for phylogenetic analysis. We have released cognac as an R package (https://github.com/rdcrawford/cognac) with customizable parameters for adaptation to diverse applications.

scholarly journals An efficient coalescent epoch model for Bayesian phylogenetic inference

2021 ◽  
Author(s):  
Remco Bouckaert
Keyword(s):  
Monte Carlo ◽  
Population Size ◽  
Graphical User Interface ◽  
Genomic Data ◽  
Phylogenetic Inference ◽  
Population Sizes ◽  
Calibrated Simulation ◽  
User Friendly ◽  
Bayesian Phylogenetic Inference ◽  
Friendly Graphical User Interface

We present a two headed approach called Bayesian Integrated Coalescent Epoch PlotS (BICEPS) for efficient inference of coalescent epoch models. Firstly, we integrate out population size parameters and secondly we introduce a set of more powerful Markov chain Monte Carlo (MCMC) proposals for flexing and stretching trees. Even though population sizes are integrated out and not explicitly sampled through MCMC, we are still able to generate samples from the population size posteriors, which allows demographic reconstruction through time. Altogether, BICEPS can be considered a more muscular version of the popular Bayesian skyline model. We demonstrate its power and correctness by a well calibrated simulation study. Furthermore, we demonstrate with an application to COVID-19 genomic data that some analyses that have trouble converging with the traditional Bayesian skyline prior and standard MCMC proposals can do well with the BICEPS approach. BICEPS is available as open source package for BEAST 2 under GPL license and has a user friendly graphical user interface.

Pedigree and Pedigree Import Wizard

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 552g-553
Author(s):  
Shahrokh Khandizadeh
Keyword(s):  
Additional Data ◽  
File Format ◽  
Fruit Crops ◽  
Operating Environment ◽  
Agronomic Characteristics ◽  
Link Type ◽  
Plant Characteristics ◽  
User Friendly

Pedigree for Windows is a user-friendly program that allows the user to trace agronomic characteristics, draw pedigrees, and view images of several fruit crops, including more than 1400 apple, 800 strawberry, 800 almond, 100 blackberry, 80 blueberry, 790 pear, 200 raspberry examples. Pedigree Import Wizard®© for Windows is an add-on software for users who are interested in importing their research or breeding data records of fruit, flower, and plant characteristics and any related images into Pedigree for Windows. Pedigree for Windows and Pedigree Import Wizard have been designed so that a user familiar with the Windows operating environment should have little need to refer to the documentation provided with the program. Pedigree Import Wizard uses a comma-separated value (csv) file format under the MS Excel environment. This option allows the user to add or import additional data to the existing database that are already stored in other software such as Lotus, Excel, Access, QuattroPro, WordPerfect, and MS Word tables, etc., as long as they work under the Windows environment. A free demo version of Pedigree and Pedigree Import Wizard for Windows is available from http://www.pgris.com.

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