DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets

DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets

Advance Access publication September 18, 2017 | Julio Rozas,1, Albert Ferrer-Mata,1 Juan Carlos Sánchez-DelBarrio,1 Sara Guirao-Rico,2 Pablo Librado,1,3 Sebastián E. Ramos-Onsins,2 and Alejandro Sánchez-Gracia1
The article introduces DnaSP 6, an updated version of the popular software for comprehensive population genetic analysis of DNA sequence data. Key features of DnaSP 6 include: 1. **New Functionalities for Large Data Sets**: The software now supports genomic partitioning methods such as RADseq and hybrid enrichment, enabling efficient analysis of high-throughput sequencing data. 2. **Faster Methods**: Scalable methods for high-throughput sequencing data are implemented, enhancing computational efficiency. 3. **Summary Statistics for Multi-Locus Analysis**: New modules for analyzing multi-locus population genetics data are included. 4. **Coalescent Simulations**: DnaSP 6 introduces modules for single- and multi-locus coalescent simulations under various demographic scenarios. 5. **Enhanced User Interface**: The program is now available with extensive documentation and is freely accessible at http://www.ub.edu/dnasp. The article also highlights the software's ability to handle large data sets, including those from RADseq and hybrid enrichment approaches, and its performance in processing and analyzing haplotype-frequency data. Benchmarking results show that DnaSP 6 can efficiently manage and analyze large data files, making it suitable for diverse applications in population genomics, molecular ecology, and clinical virology.The article introduces DnaSP 6, an updated version of the popular software for comprehensive population genetic analysis of DNA sequence data. Key features of DnaSP 6 include: 1. **New Functionalities for Large Data Sets**: The software now supports genomic partitioning methods such as RADseq and hybrid enrichment, enabling efficient analysis of high-throughput sequencing data. 2. **Faster Methods**: Scalable methods for high-throughput sequencing data are implemented, enhancing computational efficiency. 3. **Summary Statistics for Multi-Locus Analysis**: New modules for analyzing multi-locus population genetics data are included. 4. **Coalescent Simulations**: DnaSP 6 introduces modules for single- and multi-locus coalescent simulations under various demographic scenarios. 5. **Enhanced User Interface**: The program is now available with extensive documentation and is freely accessible at http://www.ub.edu/dnasp. The article also highlights the software's ability to handle large data sets, including those from RADseq and hybrid enrichment approaches, and its performance in processing and analyzing haplotype-frequency data. Benchmarking results show that DnaSP 6 can efficiently manage and analyze large data files, making it suitable for diverse applications in population genomics, molecular ecology, and clinical virology.
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[slides] DnaSP 6%3A DNA Sequence Polymorphism Analysis of Large Data Sets. | StudySpace