W-IQ-TREE is a fast and user-friendly web-based tool for maximum likelihood phylogenetic analysis. It provides an intuitive interface and server for IQ-TREE, an efficient phylogenetic software. W-IQ-TREE supports various sequence types (DNA, protein, codon, binary, morphology) in common alignment formats and a wide range of evolutionary models, including mixture and partition models. It performs fast model selection, partition scheme finding, efficient tree reconstruction, ultrafast bootstrapping, branch tests, and tree topology tests. All computations are conducted on a dedicated computer cluster, and results are delivered via URL or email. W-IQ-TREE is freely available at http://iqtree.cibiv.univie.ac.at and requires no login. IQ-TREE, the software behind W-IQ-TREE, is a versatile tool for maximum likelihood analysis of large phylogenetic data. It efficiently explores tree space and often achieves higher likelihoods than RAxML and PhyML. Key features include fast model selection, partitioned analysis for phylogenomic data, ultrafast bootstrap approximation, and branch and tree topology tests. W-IQ-TREE accepts input alignments in PHYLIP, FASTA, Nexus, Clustal, or MSF formats. It supports various sequence data types, including binary and morphological data. Users can specify substitution models and rate heterogeneity models. It uses Bayesian information criterion (BIC) or Akaike information criterion (AIC) for model selection. For phylogenomic data, it determines the best-fit partitioning scheme using PartitionFinder. IQ-TREE uses a stochastic algorithm to sample local optima in the tree space. It maintains a set of candidate trees and applies an evolutionary search algorithm to improve them. The search parameters p and c control the perturbation strength and number of iterations. W-IQ-TREE provides methods to assess branch reliability, including standard bootstrap, SH-aLRT, aBayes test, and ultrafast bootstrap (UFBoot). It also evaluates tree topology using the KH, SH, AU, and expected likelihood weight tests. After job submission, W-IQ-TREE provides a URL for job monitoring and sends email notifications. It displays the tree for quick assessment and allows users to download results in various formats. Users can also repeat the analysis locally using a command line. W-IQ-TREE is freely accessible and available on the IQ-TREE homepage. It is developed using JavaScript and Sencha framework, and the server code is written in PHP. The source code is available upon request, along with tutorials and documentation.W-IQ-TREE is a fast and user-friendly web-based tool for maximum likelihood phylogenetic analysis. It provides an intuitive interface and server for IQ-TREE, an efficient phylogenetic software. W-IQ-TREE supports various sequence types (DNA, protein, codon, binary, morphology) in common alignment formats and a wide range of evolutionary models, including mixture and partition models. It performs fast model selection, partition scheme finding, efficient tree reconstruction, ultrafast bootstrapping, branch tests, and tree topology tests. All computations are conducted on a dedicated computer cluster, and results are delivered via URL or email. W-IQ-TREE is freely available at http://iqtree.cibiv.univie.ac.at and requires no login. IQ-TREE, the software behind W-IQ-TREE, is a versatile tool for maximum likelihood analysis of large phylogenetic data. It efficiently explores tree space and often achieves higher likelihoods than RAxML and PhyML. Key features include fast model selection, partitioned analysis for phylogenomic data, ultrafast bootstrap approximation, and branch and tree topology tests. W-IQ-TREE accepts input alignments in PHYLIP, FASTA, Nexus, Clustal, or MSF formats. It supports various sequence data types, including binary and morphological data. Users can specify substitution models and rate heterogeneity models. It uses Bayesian information criterion (BIC) or Akaike information criterion (AIC) for model selection. For phylogenomic data, it determines the best-fit partitioning scheme using PartitionFinder. IQ-TREE uses a stochastic algorithm to sample local optima in the tree space. It maintains a set of candidate trees and applies an evolutionary search algorithm to improve them. The search parameters p and c control the perturbation strength and number of iterations. W-IQ-TREE provides methods to assess branch reliability, including standard bootstrap, SH-aLRT, aBayes test, and ultrafast bootstrap (UFBoot). It also evaluates tree topology using the KH, SH, AU, and expected likelihood weight tests. After job submission, W-IQ-TREE provides a URL for job monitoring and sends email notifications. It displays the tree for quick assessment and allows users to download results in various formats. Users can also repeat the analysis locally using a command line. W-IQ-TREE is freely accessible and available on the IQ-TREE homepage. It is developed using JavaScript and Sencha framework, and the server code is written in PHP. The source code is available upon request, along with tutorials and documentation.